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<!DOCTYPE html>
<html lang="en">
<head>
<title>Accessible Data Visualization in R: Color Vision and Contrast</title>
<meta charset="utf-8">
<meta name="Description" content="Make accessible data visualization in R: learn color vision deficiency, colorblind-safe palettes, WCAG contrast ratios, and redundant encoding in ggplot2.">
<meta name="Keywords" content="accessible data visualization, colorblind ggplot2, color vision deficiency, colorblind-safe palette, WCAG contrast ratio, relative luminance R, Okabe-Ito palette, viridis R, redundant encoding">
<meta name="Distribution" content="Global">
<meta name="Author" content="Selva Prabhakaran">
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.sidebar-tools-list{margin:0;padding:0;list-style:none}
.sidebar-tools-list li a{display:block;padding:5px 10px 5px 24px;font-size:14px;color:#495057;text-decoration:none;border-left:2px solid transparent;border-radius:0 4px 4px 0}
.sidebar-section-header{padding:7px 12px;font-size:15px;font-weight:700;color:#212529;cursor:pointer;border-radius:4px}
.sidebar-chevron{display:inline-block;font-size:10px;margin-right:4px;color:#757575}
.sidebar-section-items{display:none;padding-left:0;margin:2px 0 6px}
.sidebar-section.expanded .sidebar-section-items{display:block}
.sidebar-section-items li{line-height:1.5}
.sidebar-section-items li a{display:block;padding:4px 10px 4px 32px;font-size:14px;color:#495057;text-decoration:none;border-left:2px solid transparent;border-radius:0 4px 4px 0}
.sidebar-divider{margin:12px 0 2px;padding:0 12px 4px 24px;font-size:11px;font-weight:700;letter-spacing:0.06em;text-transform:uppercase;color:#9ca3af;border-bottom:1px solid #f0f2f5;list-style:none}
.sidebar-divider:first-child{margin-top:4px}
.progress-dot{display:inline-block;width:10px;height:10px;border-radius:50%;border:1.5px solid #d1d5db;margin-right:7px;vertical-align:middle;flex-shrink:0;position:relative}
/* Empty progress-dot (no status class) reads as an unchecked todo /
disabled radio next to every sidebar item — visual noise that doesn't
belong in a nav. Reserve the layout slot but hide the circle until
the item actually has progress. visibility:hidden (not display:none)
keeps the width stable when state flips. */
.progress-dot:not(.started):not(.visited):not(.completed){visibility:hidden}
/* CLS prevention: TOC sidebar matches main.css final state */
#toc-wrapper{position:sticky;top:20px;max-height:calc(100vh - 40px);overflow-y:auto;padding-left:14px;border-left:1px solid #e9ecef}
.toc-title{font-size:11px;font-weight:600;text-transform:uppercase;letter-spacing:0.8px;color:#6c757d;margin-bottom:10px;padding-bottom:0}
#toc{margin:0;padding:0}
#toc li{line-height:1.45;margin-bottom:1px}
#toc li a{font-size:13.5px;color:#6c757d;text-decoration:none;display:block;padding:3px 0;border-left:2px solid transparent;padding-left:8px;margin-left:-15px}
#toc li a.toc-active{color:#1d3158;font-weight:600;border-left-color:#1d3158}
/* CLS prevention: engagement strip layout (matches engagement.css) */
.engagement-header{display:flex;flex-wrap:wrap;align-items:center;gap:6px 10px;font-family:'Inter',-apple-system,BlinkMacSystemFont,'Segoe UI',sans-serif;font-size:12px;color:#64748b;letter-spacing:0.01em;margin:0.4em 0 1em;min-height:22px}
.engagement-header:empty{display:none}
/* CLS prevention: progress bar space (matches engagement.css) */
.engagement-progress{min-height:32px;margin:1.2em 0 1.6em}
/* CLS prevention: WebR editor min-height so the static→textarea swap doesn't shift layout */
.webr-editor{min-height:60px}
/* CLS prevention: images in content always reserve aspect ratio */
#content img{max-width:100%;height:auto}
/* =====================================================
LAYOUT V2 (opt-in via body.layout-v2). Retry 2026-05-29.
Differences from the first attempt:
1. Sidebar columns use clamp(180px, 16vw, 260px) so they
SHRINK on narrow viewports (first attempt used minmax
which pinned both sides at 260px, squeezing content on
typical laptops to ~460px).
2. Sidebar links get overflow-wrap so long tutorial titles
don't escape the narrower column.
3. min-width:0 on every grid child so they can shrink.
4. Right TOC breakpoint raised from 1100px -> 1280px so it
only shows when the viewport can actually afford it.
5. The inline-code background restyle is dropped - kept
current syntax-highlighter behavior.
All rules scoped under body.layout-v2 so pages without it
render identically.
===================================================== */
body.layout-v2{
--lv2-bg:#f8f9fb;--lv2-card:#fff;--lv2-ink:#0d1117;
--lv2-mut:#4b5260;--lv2-faint:#5b6573;
--lv2-navy:#1c2c4f;--lv2-navy-h:#2d4173;--lv2-navy-soft:#eef1f7;
--lv2-accent:#2056d2;--lv2-accent-soft:#e9efff;
--lv2-line:#e4e7ee;--lv2-border:#d4d9e3;
--lv2-green:#15803d;
background:var(--lv2-bg);color:var(--lv2-ink);
}
html.dark body.layout-v2{
--lv2-bg:#0a0f1c;--lv2-card:#0f1525;--lv2-ink:#eef2fa;
--lv2-mut:#a5afc4;--lv2-faint:#9aa6c0;
--lv2-navy:#5170b3;--lv2-navy-h:#6587c4;--lv2-navy-soft:#192240;
--lv2-accent:#7faaff;--lv2-accent-soft:#1a2748;
--lv2-line:#1f2a48;--lv2-border:#2c3a62;
}
/* Wider container; clamp-based grid that scales with viewport.
width:auto is REQUIRED because the base critical CSS has
@media(min-width:1200px){.container{width:1170px}} which would
otherwise pin width to 1170 and ignore max-width:1340. */
body.layout-v2 .container{max-width:1340px;width:auto;padding:0 22px}
body.layout-v2 .row{
display:grid;
grid-template-columns:
clamp(180px, 16vw, 260px)
minmax(0, 1fr)
clamp(180px, 16vw, 260px);
gap:0;margin-left:0;margin-right:0;
}
/* Bootstrap inserts .row::before AND .row::after pseudo-elements
(content:" "; display:table) as a clearfix. Under display:grid
these pseudos count as grid items. ::before grabs col 1, pushing
every real child one column to the right and wrapping the last
child to a new row. The 2026-05-29 first attempt only disabled
::after, resulting in nav in col 2, content in col 3, and toc
wrapping to a new row at col 1 (the bug the user reported as
"sidebar wide, content narrow"). BOTH pseudos must be killed. */
body.layout-v2 .row::before,
body.layout-v2 .row::after{display:none;content:none}
/* min-width:0 lets grid children shrink below their content's
intrinsic min-width; without this, long unbreakable text in any
child forces the column wider than the grid template intended. */
/* Drop Bootstrap's float and width on the legacy .col-sm-* hooks
so the parent .row's CSS grid owns sizing. DO NOT zero horizontal
padding here — per-column padding lives in the dedicated rules
below (sidebar, #content, #toc-sidebar) and gives the article
the 44px breathing room the mock has. */
body.layout-v2 #nav.col-sm-3,
body.layout-v2 #content.col-sm-7,
body.layout-v2 #toc-sidebar.col-sm-2{
width:auto!important;float:none!important;
min-width:0;min-height:0;
}
body.layout-v2 #nav.col-sm-3{
padding:14px 10px 40px;border-right:1px solid var(--lv2-line);
position:sticky;top:60px;height:calc(100vh - 60px);overflow-y:auto;
}
/* Inner #sidebar-nav had its own sticky + overflow from the legacy critical
CSS; under layout-v2 the outer #nav owns scrolling, so flatten the inner
one to avoid a double scrollbar. */
body.layout-v2 #sidebar-nav{
position:static;max-height:none;overflow:visible;padding:0;
}
/* Wrap long tutorial titles in the sidebar so they never overflow */
body.layout-v2 #nav a,
body.layout-v2 #nav span,
body.layout-v2 #sidebar-nav a,
body.layout-v2 #sidebar-nav li{
overflow-wrap:break-word;word-break:break-word;
}
body.layout-v2 #content{padding:24px 44px 60px}
/* S3 — Code-block bottom spacing.
Default .webr-container margin is 22/22; the dark block visually
carries a lot of weight, so the next paragraph reads as cramped.
Lift bottom to 30px under layout-v2. */
body.layout-v2 #content .webr-container{margin-bottom:30px}
/* S7 — Further Reading: convert auto-injected <ul> to a 2-column
card grid that matches the .rt-grid pattern used elsewhere.
No HTML/auto_link.py changes needed — pure CSS. */
body.layout-v2 #content #auto-further-reading .further-reading-list{
list-style:none;padding:0;margin:14px 0 0;
display:grid;grid-template-columns:repeat(2,minmax(0,1fr));gap:12px;
}
body.layout-v2 #content #auto-further-reading .further-reading-list li{margin:0}
body.layout-v2 #content #auto-further-reading .further-reading-list li a{
display:block;padding:14px 16px;
background:var(--lv2-card);border:1px solid var(--lv2-border);
border-radius:8px;color:var(--lv2-ink);
font-weight:500;font-size:15px;line-height:1.4;
text-decoration:none;
transition:border-color .15s,background .15s,transform .15s;
}
body.layout-v2 #content #auto-further-reading .further-reading-list li a:hover{
border-color:var(--lv2-accent);background:var(--lv2-accent-soft);
text-decoration:none;transform:translateY(-1px);
}
@media(max-width:820px){
body.layout-v2 #content #auto-further-reading .further-reading-list{
grid-template-columns:1fr;
}
}
body.layout-v2 #toc-sidebar{padding:24px 18px;position:sticky;top:74px;align-self:start}
@media(max-width:1280px){
body.layout-v2 .row{grid-template-columns:clamp(180px, 18vw, 260px) minmax(0,1fr)}
body.layout-v2 #toc-sidebar{display:none}
}
@media(max-width:820px){
body.layout-v2 .row{grid-template-columns:1fr}
body.layout-v2 #nav{display:none}
body.layout-v2 #content{padding:20px}
}
/* Typography refresh - sized to mock spec */
body.layout-v2 #content{
font-size:16.5px;line-height:1.7;color:var(--lv2-ink);
font-feature-settings:"tnum","ss01","cv11";text-rendering:optimizeLegibility;
}
body.layout-v2 #content p{line-height:1.7;margin:13px 0;color:var(--lv2-ink);text-wrap:pretty}
body.layout-v2 #content h1{
font-size:38px;font-weight:700;line-height:1.2;letter-spacing:-0.018em;
margin:10px 0 13px;text-wrap:balance;color:var(--lv2-ink);
}
/* H2: hairline divider + breathing room above. Mock breaks each
section with a top rule and ~48px space; staging used 34px and no
divider, leaving sections to blur together. :first-of-type keeps
the very first H2 flush with the actionbar (no double divider). */
body.layout-v2 #content h2{
font-size:25px;font-weight:600;line-height:1.25;letter-spacing:-0.018em;
margin:48px 0 12px;padding-top:32px;border-top:1px solid var(--lv2-line);
text-wrap:balance;color:var(--lv2-ink);
}
body.layout-v2 #content h2:first-of-type{
margin-top:24px;padding-top:0;border-top:none;
}
body.layout-v2 #content h3,body.layout-v2 #content h4{
font-size:18px;font-weight:600;line-height:1.3;margin:24px 0 8px;text-wrap:balance;color:var(--lv2-ink);
}
/* Specificity bump: `body.layout-v2 #content p` (1 id + 1 class
+ 2 elements) was beating `body.layout-v2 p.lead` (2 classes +
2 elements) and forcing the dek to var(--lv2-ink) instead of
var(--lv2-mut). Adding #content here matches that specificity. */
body.layout-v2 #content p.lead{
font-size:18.5px;line-height:1.6;color:var(--lv2-mut);
border-left:3px solid var(--lv2-navy);padding-left:17px;margin:-2px 0 20px;font-weight:400;
}
/* Body link color: legacy a{color:#1d3158} and Bootstrap .text-muted
leave inline links almost indistinguishable from body text. Use
the mock accent so links are obviously clickable. Excludes
buttons, cards, prev/next nav, and TOC items which have their
own palette. */
body.layout-v2 #content a:not(.btn):not(.rt-card):not(.pn-link):not(.lv2-anchor):not([class*="toc"]){
color:var(--lv2-accent);
}
body.layout-v2 #content a:not(.btn):not(.rt-card):not(.pn-link):not(.lv2-anchor):not([class*="toc"]):hover{
text-decoration:underline;
}
/* Inline <code> palette: match the mock's navy-soft tint instead
of the legacy purple-blue (#eef vs #eef1f7). */
body.layout-v2 #content :not(pre) > code{
background:var(--lv2-navy-soft);color:var(--lv2-ink);
border-radius:4px;padding:2px 5px;font-size:0.92em;
}
/* TOC right rail */
body.layout-v2 #toc-sidebar .toc-title{font-size:10.5px;font-weight:700;text-transform:uppercase;letter-spacing:.08em;color:var(--lv2-faint);margin-bottom:9px}
body.layout-v2 #toc{font-size:13px}
body.layout-v2 #toc li{margin:0;line-height:1.45}
body.layout-v2 #toc li a{
display:block;padding:5px 0 5px 11px;
border-left:2px solid var(--lv2-line);
color:var(--lv2-faint);font-size:13px;
transition:color .15s,border-color .15s;
}
body.layout-v2 #toc li a:hover{color:var(--lv2-ink)}
body.layout-v2 #toc li a.toc-active{
border-left-color:var(--lv2-navy);color:var(--lv2-ink);font-weight:600;
}
/* Reading progress bar - uses transform:scaleX so we don't fight any
containing-block / overflow quirks that can pin a width-% bar to 0. */
.lv2-progress{
position:fixed;top:0;left:0;width:100vw;height:3px;
background:var(--lv2-accent,#2056d2);z-index:90;
transform:scaleX(0);transform-origin:left center;
transition:transform .1s ease-out;pointer-events:none;
}
/* Heading anchor links (hover-reveal) */
body.layout-v2 #content h2,
body.layout-v2 #content h3,
body.layout-v2 #content h4{position:relative}
body.layout-v2 .lv2-anchor{
position:absolute;left:-26px;top:50%;transform:translateY(-50%);
font-size:.55em;color:var(--lv2-faint);text-decoration:none;
opacity:0;transition:opacity .15s,color .15s;
cursor:pointer;padding:4px 6px;line-height:1;font-weight:400;
}
body.layout-v2 #content h2:hover .lv2-anchor,
body.layout-v2 #content h3:hover .lv2-anchor,
body.layout-v2 #content h4:hover .lv2-anchor,
body.layout-v2 .lv2-anchor:focus-visible{opacity:1}
body.layout-v2 .lv2-anchor:hover{color:var(--lv2-accent)}
@media(max-width:820px){body.layout-v2 .lv2-anchor{left:0;top:-22px;transform:none}}
/* Focus ring refresh */
body.layout-v2 a:focus-visible,
body.layout-v2 button:focus-visible,
body.layout-v2 input:focus-visible,
body.layout-v2 textarea:focus-visible{
outline:none;
box-shadow:0 0 0 3px rgba(32,86,210,.22);
border-radius:4px;
}
html.dark body.layout-v2 a:focus-visible,
html.dark body.layout-v2 button:focus-visible,
html.dark body.layout-v2 input:focus-visible{box-shadow:0 0 0 3px rgba(127,170,255,.22)}
/* Reduced motion: shut everything down for users who request it */
@media (prefers-reduced-motion: reduce){
body.layout-v2 *,body.layout-v2 *::before,body.layout-v2 *::after{
animation-duration:0.01ms!important;
animation-iteration-count:1!important;
transition-duration:0.01ms!important;
scroll-behavior:auto!important;
}
}
</style>
<!-- Full Bootstrap deferred (non-render-blocking) -->
<link href="www/bootstrap.min.css?h=dae0a568" rel="stylesheet" media="print" onload="this.media='all'">
<noscript><link href="www/bootstrap.min.css?h=dae0a568" rel="stylesheet"></noscript>
<!-- Roadmap-jel: load code-highlight CSS normally (not deferred) so code blocks paint COLORED on first load, not after interaction. Small file; negligible render cost. -->
<link href="www/highlight.min.css?h=f103014a" rel="stylesheet">
<link href="css/main.min.css?h=78c68235" rel="stylesheet" media="print" onload="this.media='all'">
<noscript><link href="css/main.min.css?h=78c68235" rel="stylesheet"></noscript>
<!-- Sitewide navbar (canonical roadmap .nav design). Loaded sync: the nav
is above the fold and must never flash unstyled. -->
<link href="/www/site-nav.css?v=19" rel="stylesheet">
<style>
a{color:#1d3158}a:hover{text-decoration:underline}
li{line-height:1.65}
.MathJax_Display{margin:0}
blockquote p{line-height:1.75;color:#717171}
/* engagement.js renders a meta strip into .engagement-header that
duplicates the byline (difficulty + time). Hide it; saved-posts-
button.js reads the data-* attrs directly for the byline. */
.engagement-header{display:none!important}
/* Byline (saved-posts widget rebuilds this after H1+lead, mock-style) */
.byline{display:flex;flex-wrap:wrap;align-items:center;gap:8px;
font-size:13.5px;color:#4b5260;margin:6px 0 16px;line-height:1.5}
/* P1 — bump avatar 26→30 to match mock visual weight. */
.byline .av-sm{width:30px;height:30px;border-radius:50%;
background:linear-gradient(135deg,#1c2c4f,#2d4173);color:#fff;
display:inline-flex;align-items:center;justify-content:center;
font-weight:700;font-size:12px;flex:none;letter-spacing:.02em}
.byline .who{color:#0d1117;font-weight:600}
.byline .dot{color:#c0c5cf}
.byline .rev{color:#137a3e;font-weight:600;display:inline-flex;align-items:center;gap:4px}
.byline .time{display:inline-flex;align-items:center;gap:4px;color:#6b7280}
.byline .diff{font-size:10.5px;font-weight:700;text-transform:uppercase;
letter-spacing:.05em;background:#eef1f7;color:#4b5260;
padding:3px 8px;border-radius:999px;margin-left:2px}
/* Action bar (saved-posts widget injects this after byline) */
.actionbar{display:flex;align-items:center;gap:9px;margin:10px 0 26px;padding:12px 0;
border-top:1px solid #e4e7ee;border-bottom:1px solid #e4e7ee;flex-wrap:wrap}
.actionbar .act{display:inline-flex;align-items:center;gap:6px;border:1px solid #d4d9e3;
background:#fff;border-radius:9px;padding:7px 12px;font-size:13px;font-weight:600;
color:#4b5260;cursor:pointer;font-family:inherit;
transition:border-color .15s,color .15s,background .15s}
.actionbar .act:hover{border-color:#0a0d14;color:#0a0d14}
.actionbar .act.bookmark-btn[data-saved="1"]{background:#fef3c7;border-color:#f59e0b;color:#92400e}
.actionbar .act.bookmark-btn[data-saved="1"] svg{fill:#f59e0b}
.actionbar .act:disabled{opacity:.55;cursor:wait}
.actionbar-sync{margin-left:auto;font-size:12px;color:#6b7280}
.actionbar-sync a{color:#2056d2;font-weight:600;text-decoration:none}
.actionbar-sync a:hover{text-decoration:underline}
/* Dark-mode overrides for byline + actionbar. The hard-coded #0d1117
on .who renders invisible on the dark background; the action-bar
borders and surfaces also need to flip. Tokens (--lv2-ink, --lv2-mut,
--lv2-line, --lv2-card) already swap under html.dark body.layout-v2;
we just need to point the hard-coded rules at them under dark. */
html.dark body.layout-v2 .byline{color:var(--lv2-mut)}
html.dark body.layout-v2 .byline .who{color:var(--lv2-ink)}
html.dark body.layout-v2 .byline .dot{color:var(--lv2-faint)}
html.dark body.layout-v2 .byline .time{color:var(--lv2-mut)}
html.dark body.layout-v2 .byline .diff{background:var(--lv2-navy-soft);color:var(--lv2-mut)}
html.dark body.layout-v2 .actionbar{border-top-color:var(--lv2-line);border-bottom-color:var(--lv2-line)}
html.dark body.layout-v2 .actionbar .act{background:var(--lv2-card);border-color:var(--lv2-border);color:var(--lv2-mut)}
html.dark body.layout-v2 .actionbar .act:hover{border-color:var(--lv2-ink);color:var(--lv2-ink)}
html.dark body.layout-v2 .actionbar-sync{color:var(--lv2-mut)}
/* Toast (Share button "Link copied" feedback) */
.rs-toast{position:fixed;bottom:24px;left:50%;transform:translateX(-50%) translateY(8px);
background:#0a0d14;color:#fff;padding:9px 18px;border-radius:8px;font-size:13px;
font-family:'IBM Plex Sans',sans-serif;z-index:1000;opacity:0;pointer-events:none;
transition:opacity .2s,transform .2s;box-shadow:0 8px 24px rgba(10,13,20,.25)}
.rs-toast.show{opacity:1;transform:translateX(-50%) translateY(0)}
/* Auth-state visibility helpers (used by masthead variants) */
.auth-anon,.auth-user{display:none}
body.state-anon .auth-anon{display:inline-flex;align-items:center}
body.state-pro .auth-user{display:inline-flex;align-items:center;gap:8px}
.auth-signout.masthead-icon-btn{background:none;border:1px solid #d8dce2;border-radius:6px;padding:4px 9px;font-size:14px;line-height:1;color:#4a5160;cursor:pointer;transition:border-color .15s,color .15s}
.auth-signout.masthead-icon-btn:hover{border-color:#9a1f1f;color:#9a1f1f}
html.dark .auth-signout.masthead-icon-btn{border-color:#262a31;color:#c3cad9}
html.dark .auth-signout.masthead-icon-btn:hover{border-color:#f08989;color:#f08989}
@media(min-width:1200px){.container{width:1170px}}
#nav,#content,#toc-sidebar{box-sizing:border-box}
#content{padding-left:15px;padding-right:15px;overflow-wrap:break-word;word-wrap:break-word;overflow-x:clip}
@media(max-width:767px){#nav{display:none}}
.mobile-sidebar-overlay{display:none;position:fixed;top:0;left:0;right:0;bottom:0;z-index:9999;background:rgba(0,0,0,0.4)}
.mobile-sidebar-overlay.open{display:block}
.mobile-sidebar-panel{position:fixed;top:0;left:0;bottom:0;width:280px;background:#fff;z-index:10000;overflow-y:auto;padding:16px;box-shadow:2px 0 16px rgba(0,0,0,0.15);transform:translateX(-100%);transition:transform 0.25s ease}
.mobile-sidebar-overlay.open .mobile-sidebar-panel{transform:translateX(0)}
.mobile-sidebar-close{position:absolute;top:10px;right:12px;background:none;border:none;font-size:22px;cursor:pointer;color:#666}
/* Mobile top-nav drawer section */
.mnav-section{margin-bottom:18px;padding-bottom:14px;border-bottom:1px solid #e5e7eb}
.mnav-section:last-child{border-bottom:none}
.mnav-title{font-family:'IBM Plex Sans',sans-serif;font-size:11px;font-weight:600;color:#8a8f99;text-transform:uppercase;letter-spacing:0.06em;margin:0 0 8px}
.mnav-link{display:block;padding:9px 10px;color:#3a3f4a;text-decoration:none;font-size:15px;border-radius:6px;font-family:'IBM Plex Sans',sans-serif}
.mnav-link:hover,.mnav-link:active{background:#f1f3f6;color:#0d1117;text-decoration:none}
.mnav-accordion{padding:0}
.mnav-accordion>summary{padding:9px 10px;cursor:pointer;font-size:15px;font-weight:500;color:#3a3f4a;list-style:none;border-radius:6px;font-family:'IBM Plex Sans',sans-serif;display:flex;align-items:center;justify-content:space-between}
.mnav-accordion>summary::-webkit-details-marker{display:none}
.mnav-accordion>summary::after{content:'\25BE';font-size:11px;color:#8a8f99;transition:transform 0.15s}
.mnav-accordion[open]>summary::after{transform:rotate(180deg)}
.mnav-accordion>summary:hover{background:#f1f3f6}
.mnav-accordion-body{padding:4px 6px 8px 10px}
.mnav-accordion-body .mnav-link{padding:7px 8px;font-size:14px;color:#4a5160}
.mnav-accordion-body h6{margin:10px 0 4px 8px;font-family:'IBM Plex Sans',sans-serif;font-size:10px;font-weight:600;color:#8a8f99;text-transform:uppercase;letter-spacing:0.06em}
html.dark .mobile-sidebar-panel{background:#1e293b}
html.dark .mobile-sidebar-overlay{background:rgba(0,0,0,0.6)}
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class="subsec-chevron">▼</span> R Fundamentals</li><li data-subkey="sec0sub2"><a href="/R-Syntax-101.html" title="R Syntax 101"><span class="progress-dot"></span>R Syntax 101</a></li><li data-subkey="sec0sub2"><a href="/R-Data-Types.html" title="R Data Types"><span class="progress-dot"></span>R Data Types</a></li><li data-subkey="sec0sub2"><a href="/R-Vectors.html" title="R Vectors"><span class="progress-dot"></span>R Vectors</a></li><li data-subkey="sec0sub2"><a href="/R-Matrices.html" title="R Matrices"><span class="progress-dot"></span>R Matrices</a></li><li data-subkey="sec0sub2"><a href="/R-Factors.html" title="R Factors"><span class="progress-dot"></span>R Factors</a></li><li data-subkey="sec0sub2"><a href="/R-Data-Frames.html" title="R Data Frames"><span class="progress-dot"></span>R Data Frames</a></li><li data-subkey="sec0sub2"><a href="/R-Lists.html" title="R Lists"><span class="progress-dot"></span>R Lists</a></li><li data-subkey="sec0sub2"><a href="/R-Control-Flow.html" title="R Control Flow"><span class="progress-dot"></span>R Control Flow</a></li><li data-subkey="sec0sub2"><a href="/R-Special-Values.html" title="R Special Values"><span class="progress-dot"></span>R Special Values</a></li><li data-subkey="sec0sub2"><a href="/R-Type-Coercion.html" title="R Type Coercion"><span class="progress-dot"></span>R Type Coercion</a></li><li data-subkey="sec0sub2"><a href="/R-Functions.html" title="Writing R Functions"><span class="progress-dot"></span>Writing R Functions</a></li><li data-subkey="sec0sub2" class="is-quiz"><a href="/R-Beginner-Exercises-quiz.html" title="R Fundamentals Quiz"><span class="quiz-marker" aria-hidden="true"><svg viewBox="0 0 24 24" fill="currentColor" aria-hidden="true"><path d="M12 2 4 5.1v5.7c0 4.9 3.4 8.4 8 9.9 4.6-1.5 8-5 8-9.9V5.1L12 2z"/></svg></span>Quiz</a></li><li class="sidebar-divider sidebar-subsection-toggle" data-subkey="sec0sub3" data-collapsed="false"><span class="subsec-chevron">▼</span> Working Effectively</li><li data-subkey="sec0sub3"><a href="/R-Subsetting.html" title="R Subsetting"><span class="progress-dot"></span>R Subsetting</a></li><li data-subkey="sec0sub3"><a href="/Getting-Help-in-R.html" title="Getting Help in R"><span class="progress-dot"></span>Getting Help in R</a></li><li data-subkey="sec0sub3"><a href="/R-Project-Structure.html" title="R Project Structure"><span class="progress-dot"></span>R Project Structure</a></li><li class="sidebar-divider sidebar-subsection-toggle" data-subkey="sec0sub4" data-collapsed="false"><span class="subsec-chevron">▼</span> R Career & Resources</li><li data-subkey="sec0sub4"><a href="/R-vs-Python.html" title="R vs Python"><span class="progress-dot"></span>R vs Python</a></li><li data-subkey="sec0sub4"><a href="/How-to-Learn-R.html" title="How to Learn R"><span class="progress-dot"></span>How to Learn R</a></li><li data-subkey="sec0sub4"><a href="/R-for-Excel-Users.html" title="R for Excel Users"><span class="progress-dot"></span>R for Excel Users</a></li><li data-subkey="sec0sub4"><a href="/R-Interview-Questions.html" title="R Interview Questions"><span class="progress-dot"></span>R Interview Questions</a></li><li data-subkey="sec0sub4" class="is-quiz"><a href="/R-Interview-Questions-quiz.html" title="R Interview Readiness Quiz"><span class="quiz-marker" aria-hidden="true"><svg viewBox="0 0 24 24" fill="currentColor" aria-hidden="true"><path d="M12 2 4 5.1v5.7c0 4.9 3.4 8.4 8 9.9 4.6-1.5 8-5 8-9.9V5.1L12 2z"/></svg></span>Quiz</a></li><li data-subkey="sec0sub4"><a href="/R-Cheat-Sheet.html" title="R Cheat Sheet"><span class="progress-dot"></span>R Cheat Sheet</a></li><li data-subkey="sec0sub4"><a href="/Bias-in-Data-and-Models.html" title="Bias in Data and Models"><span class="progress-dot"></span>Bias in Data and Models</a></li><li data-subkey="sec0sub4"><a href="/Communicating-Uncertainty.html" title="Communicating Uncertainty"><span class="progress-dot"></span>Communicating Uncertainty</a></li><li data-subkey="sec0sub4"><a href="/Data-Ethics-in-R.html" title="Data Ethics"><span class="progress-dot"></span>Data Ethics</a></li><li data-subkey="sec0sub4"><a href="/Data-Privacy-in-R.html" title="Data Privacy in R"><span class="progress-dot"></span>Data Privacy in R</a></li><li data-subkey="sec0sub4"><a href="/R-Foundations-Basics-Course.html" title="R Foundations: The Basics (Course)"><span class="progress-dot"></span>R Foundations: The Basics (Course)</a></li><li data-subkey="sec0sub4"><a href="/R-Foundations-Debugging-Course.html" title="R Foundations: Debugging (Course)"><span class="progress-dot"></span>R Foundations: Debugging (Course)</a></li><li data-subkey="sec0sub4"><a href="/R-Foundations-Iteration-Course.html" title="R Foundations: Iteration (Course)"><span class="progress-dot"></span>R Foundations: Iteration (Course)</a></li><li data-subkey="sec0sub4"><a href="/R-Foundations-Structures-Course.html" title="R Foundations: Data Structures (Course)"><span class="progress-dot"></span>R Foundations: Data Structures (Course)</a></li><li data-subkey="sec0sub4"><a href="/R-Foundations-Workflow-Course.html" title="R Foundations: Reproducible Workflow (Course)"><span class="progress-dot"></span>R Foundations: Reproducible Workflow (Course)</a></li><li data-subkey="sec0sub4"><a href="/Reproducibility-Crisis.html" title="Reproducibility Crisis"><span class="progress-dot"></span>Reproducibility Crisis</a></li></ul></li><li class="sidebar-section expanded"><div class="sidebar-section-header"><span class="sidebar-chevron">▸</span><span class="sec-num">2.</span> <span class="sec-title-t">Data Wrangling</span><span class="section-meta" data-section-meta></span></div><ul class="sidebar-section-items list-unstyled"><li class="sidebar-divider sidebar-subsection-toggle" data-subkey="sec1sub1" data-collapsed="false"><span class="subsec-chevron">▼</span> Import & Setup</li><li data-subkey="sec1sub1"><a href="/Importing-Data-in-R.html" title="Importing Data"><span class="progress-dot"></span>Importing Data</a></li><li data-subkey="sec1sub1"><a href="/R-Pipe-Operator.html" title="Pipe Operator"><span class="progress-dot"></span>Pipe Operator</a></li><li data-subkey="sec1sub1"><a href="/Tidy-Data-in-R.html" title="Tidy Data"><span class="progress-dot"></span>Tidy Data</a></li><li class="sidebar-divider sidebar-subsection-toggle" data-subkey="sec1sub2" data-collapsed="false"><span class="subsec-chevron">▼</span> dplyr Essentials</li><li data-subkey="sec1sub2"><a href="/dplyr-filter-select.html" title="dplyr filter & select"><span class="progress-dot"></span>dplyr filter & select</a></li><li data-subkey="sec1sub2"><a href="/dplyr-mutate-rename.html" title="dplyr mutate & rename"><span class="progress-dot"></span>dplyr mutate & rename</a></li><li data-subkey="sec1sub2"><a href="/dplyr-group-by-summarise.html" title="dplyr group_by & summarise"><span class="progress-dot"></span>dplyr group_by & summarise</a></li><li data-subkey="sec1sub2"><a href="/dplyr-arrange-slice.html" title="dplyr arrange & slice"><span class="progress-dot"></span>dplyr arrange & slice</a></li><li data-subkey="sec1sub2"><a href="/dplyr-across.html" title="dplyr across()"><span class="progress-dot"></span>dplyr across()</a></li><li data-subkey="sec1sub2"><a href="/dplyr-case-when.html" title="dplyr case_when()"><span class="progress-dot"></span>dplyr case_when()</a></li><li data-subkey="sec1sub2" class="is-quiz"><a href="/dplyr-Exercises-in-R-quiz.html" title="dplyr Quiz"><span class="quiz-marker" aria-hidden="true"><svg viewBox="0 0 24 24" fill="currentColor" aria-hidden="true"><path d="M12 2 4 5.1v5.7c0 4.9 3.4 8.4 8 9.9 4.6-1.5 8-5 8-9.9V5.1L12 2z"/></svg></span>Quiz</a></li><li class="sidebar-divider sidebar-subsection-toggle" data-subkey="sec1sub3" data-collapsed="false"><span class="subsec-chevron">▼</span> Join & Reshape</li><li data-subkey="sec1sub3"><a href="/R-Joins.html" title="R Joins"><span class="progress-dot"></span>R Joins</a></li><li data-subkey="sec1sub3"><a href="/pivot_longer-pivot_wider-Reshape-Data-in-R.html" title="pivot_longer & pivot_wider"><span class="progress-dot"></span>pivot_longer & pivot_wider</a></li><li data-subkey="sec1sub3"><a href="/tidyr-separate-unite-Split-Combine-Columns-in-R.html" title="separate() & unite()"><span class="progress-dot"></span>separate() & unite()</a></li><li data-subkey="sec1sub3" class="is-quiz"><a href="/tidyr-Exercises-in-R-quiz.html" title="tidyr Quiz"><span class="quiz-marker" aria-hidden="true"><svg viewBox="0 0 24 24" fill="currentColor" aria-hidden="true"><path d="M12 2 4 5.1v5.7c0 4.9 3.4 8.4 8 9.9 4.6-1.5 8-5 8-9.9V5.1L12 2z"/></svg></span>Quiz</a></li><li class="sidebar-divider sidebar-subsection-toggle" data-subkey="sec1sub4" data-collapsed="false"><span class="subsec-chevron">▼</span> Clean & Quality</li><li data-subkey="sec1sub4"><a href="/Missing-Values-in-R-Detect-Count-Remove-Impute-NA.html" title="Missing Values (NA)"><span class="progress-dot"></span>Missing Values (NA)</a></li><li data-subkey="sec1sub4"><a href="/Data-Quality-Checking-in-R.html" title="Data Quality Checking"><span class="progress-dot"></span>Data Quality Checking</a></li><li data-subkey="sec1sub4"><a href="/janitor-Package-in-R.html" title="janitor Package"><span class="progress-dot"></span>janitor Package</a></li><li class="sidebar-divider sidebar-subsection-toggle" data-subkey="sec1sub5" data-collapsed="false"><span class="subsec-chevron">▼</span> Strings & Dates</li><li data-subkey="sec1sub5"><a href="/stringr-in-R.html" title="stringr"><span class="progress-dot"></span>stringr</a></li><li data-subkey="sec1sub5"><a href="/R-Regex-stringr-Pattern-Matching.html" title="Regex Patterns"><span class="progress-dot"></span>Regex Patterns</a></li><li data-subkey="sec1sub5"><a href="/lubridate-in-R.html" title="lubridate"><span class="progress-dot"></span>lubridate</a></li><li class="sidebar-divider sidebar-subsection-toggle" data-subkey="sec1sub6" data-collapsed="false"><span class="subsec-chevron">▼</span> Scale & Connect</li><li data-subkey="sec1sub6"><a href="/DBI-in-R.html" title="DBI & Databases"><span class="progress-dot"></span>DBI & Databases</a></li><li data-subkey="sec1sub6"><a href="/DuckDB-in-R.html" title="DuckDB & duckplyr"><span class="progress-dot"></span>DuckDB & duckplyr</a></li><li data-subkey="sec1sub6"><a href="/Web-Scraping-in-R-with-rvest.html" title="Web Scraping (rvest)"><span class="progress-dot"></span>Web Scraping (rvest)</a></li><li data-subkey="sec1sub6"><a href="/REST-APIs-in-R-with-httr2.html" title="REST APIs (httr2)"><span class="progress-dot"></span>REST APIs (httr2)</a></li><li data-subkey="sec1sub6"><a href="/Data-Wrangling-dplyr-Course.html" title="Data Wrangling with dplyr (Course)"><span class="progress-dot"></span>Data Wrangling with dplyr (Course)</a></li><li data-subkey="sec1sub6"><a href="/Join-Reshape-Course.html" title="Join & Reshape (Course)"><span class="progress-dot"></span>Join & Reshape (Course)</a></li><li data-subkey="sec1sub6"><a href="/data-table-Course.html" title="data.table (Course)"><span class="progress-dot"></span>data.table (Course)</a></li><li data-subkey="sec1sub6"><a href="/Report-Tables-Course.html" title="Report-Ready Tables (Course)"><span class="progress-dot"></span>Report-Ready Tables (Course)</a></li><li data-subkey="sec1sub6"><a href="/Communicate-Automate-Course.html" title="Communicate & Automate (Course)"><span class="progress-dot"></span>Communicate & Automate (Course)</a></li></ul></li><li class="sidebar-section expanded"><div class="sidebar-section-header"><span class="sidebar-chevron">▸</span><span class="sec-num">3.</span> <span class="sec-title-t">Statistics</span><span class="section-meta" data-section-meta></span></div><ul class="sidebar-section-items list-unstyled"><li class="sidebar-divider sidebar-subsection-toggle" data-subkey="sec2sub1" data-collapsed="false"><span class="subsec-chevron">▼</span> EDA & Data Quality</li><li data-subkey="sec2sub1"><a href="/Automated-EDA-in-R.html" title="Automated EDA"><span class="progress-dot"></span>Automated EDA</a></li><li data-subkey="sec2sub1"><a href="/Missing-Data-Visualization-in-R-naniar.html" title="Missing Data Viz (naniar)"><span class="progress-dot"></span>Missing Data Viz (naniar)</a></li><li data-subkey="sec2sub1"><a href="/Outlier-Detection-in-R.html" title="Outlier Detection"><span class="progress-dot"></span>Outlier Detection</a></li><li class="sidebar-divider sidebar-subsection-toggle" data-subkey="sec2sub2" data-collapsed="false"><span class="subsec-chevron">▼</span> Probability</li><li data-subkey="sec2sub2"><a href="/Sample-Spaces-Events-and-Probability-Axioms-in-R-With-Monte-Carlo-Proof.html" title="Probability Axioms"><span class="progress-dot"></span>Probability Axioms</a></li><li data-subkey="sec2sub2"><a href="/Conditional-Probability-in-R.html" title="Conditional Probability"><span class="progress-dot"></span>Conditional Probability</a></li><li data-subkey="sec2sub2"><a href="/Random-Variables-in-R.html" title="Random Variables"><span class="progress-dot"></span>Random Variables</a></li><li data-subkey="sec2sub2"><a href="/Binomial-and-Poisson-Distributions-in-R.html" title="Binomial vs Poisson"><span class="progress-dot"></span>Binomial vs Poisson</a></li><li data-subkey="sec2sub2"><a href="/Normal-t-F-and-Chi-Squared-Distributions-in-R.html" title="Normal, t, F, Chi-Squared"><span class="progress-dot"></span>Normal, t, F, Chi-Squared</a></li><li data-subkey="sec2sub2"><a href="/Central-Limit-Theorem-in-R.html" title="Central Limit Theorem"><span class="progress-dot"></span>Central Limit Theorem</a></li><li data-subkey="sec2sub2"><a href="/Sampling-Distributions-in-R.html" title="Sampling Distributions"><span class="progress-dot"></span>Sampling Distributions</a></li><li data-subkey="sec2sub2"><a href="/Law-of-Large-Numbers-vs-CLT-in-R.html" title="LLN vs CLT"><span class="progress-dot"></span>LLN vs CLT</a></li><li data-subkey="sec2sub2"><a href="/What-Is-Probability-Simulation-First-Intuition-in-R-Before-the-Formulas.html" title="Probability (Simulation-First)"><span class="progress-dot"></span>Probability (Simulation-First)</a></li><li data-subkey="sec2sub2"><a href="/Expected-Value-and-Variance-in-R.html" title="Expected Value and Variance"><span class="progress-dot"></span>Expected Value and Variance</a></li><li class="sidebar-divider sidebar-subsection-toggle" data-subkey="sec2sub3" data-collapsed="false"><span class="subsec-chevron">▼</span> Inference & Estimation</li><li data-subkey="sec2sub3"><a href="/Maximum-Likelihood-Estimation-in-R.html" title="Maximum Likelihood Estimation"><span class="progress-dot"></span>Maximum Likelihood Estimation</a></li><li data-subkey="sec2sub3"><a href="/Hypothesis-Testing-in-R.html" title="Hypothesis Testing"><span class="progress-dot"></span>Hypothesis Testing</a></li><li data-subkey="sec2sub3"><a href="/Sample-Size-Planning-in-R.html" title="Sample Size Planning"><span class="progress-dot"></span>Sample Size Planning</a></li><li data-subkey="sec2sub3"><a href="/Which-Statistical-Test-in-R.html" title="Choosing the Right Test"><span class="progress-dot"></span>Choosing the Right Test</a></li><li data-subkey="sec2sub3"><a href="/Statistical-Tests-in-R.html" title="Statistical Tests"><span class="progress-dot"></span>Statistical Tests</a></li><li data-subkey="sec2sub3"><a href="/Measures-of-Association-in-R.html" title="Measures of Association"><span class="progress-dot"></span>Measures of Association</a></li><li data-subkey="sec2sub3"><a href="/Point-Estimation-in-R.html" title="Point Estimation"><span class="progress-dot"></span>Point Estimation</a></li><li data-subkey="sec2sub3"><a href="/Confidence-Intervals-in-R.html" title="Confidence Intervals"><span class="progress-dot"></span>Confidence Intervals</a></li><li data-subkey="sec2sub3"><a href="/Type-I-and-Type-II-Errors-in-R.html" title="Type I and II Errors"><span class="progress-dot"></span>Type I and II Errors</a></li><li data-subkey="sec2sub3"><a href="/Statistical-Power-Analysis-in-R.html" title="Power Analysis"><span class="progress-dot"></span>Power Analysis</a></li><li data-subkey="sec2sub3"><a href="/Effect-Size-in-R.html" title="Effect Size"><span class="progress-dot"></span>Effect Size</a></li><li data-subkey="sec2sub3"><a href="/t-Tests-in-R.html" title="t-Tests"><span class="progress-dot"></span>t-Tests</a></li><li data-subkey="sec2sub3"><a href="/Proportion-Tests-in-R.html" title="Proportion Tests"><span class="progress-dot"></span>Proportion Tests</a></li><li data-subkey="sec2sub3"><a href="/Normality-and-Variance-Tests-in-R.html" title="Normality & Variance Tests"><span class="progress-dot"></span>Normality & Variance Tests</a></li><li data-subkey="sec2sub3"><a href="/Chi-Square-Tests-in-R.html" title="Chi-Square Tests"><span class="progress-dot"></span>Chi-Square Tests</a></li><li data-subkey="sec2sub3"><a href="/Wilcoxon-Mann-Whitney-and-Kruskal-Wallis-in-R.html" title="Wilcoxon, Mann-Whitney & Kruskal-Wallis"><span class="progress-dot"></span>Wilcoxon, Mann-Whitney & Kruskal-Wallis</a></li><li data-subkey="sec2sub3"><a href="/Multiple-Comparisons-in-R.html" title="Multiple Testing Correction"><span class="progress-dot"></span>Multiple Testing Correction</a></li><li data-subkey="sec2sub3" class="is-quiz"><a href="/Hypothesis-Testing-Exercises-in-R-quiz.html" title="Hypothesis Testing Quiz"><span class="quiz-marker" aria-hidden="true"><svg viewBox="0 0 24 24" fill="currentColor" aria-hidden="true"><path d="M12 2 4 5.1v5.7c0 4.9 3.4 8.4 8 9.9 4.6-1.5 8-5 8-9.9V5.1L12 2z"/></svg></span>Quiz</a></li><li class="sidebar-divider sidebar-subsection-toggle" data-subkey="sec2sub4" data-collapsed="false"><span class="subsec-chevron">▼</span> Regression</li><li data-subkey="sec2sub4"><a href="/Linear-Regression.html" title="Linear Regression"><span class="progress-dot"></span>Linear Regression</a></li><li data-subkey="sec2sub4"><a href="/Logistic-Regression-With-R.html" title="Logistic Regression"><span class="progress-dot"></span>Logistic Regression</a></li><li data-subkey="sec2sub4"><a href="/Variable-Selection-and-Importance-With-R.html" title="Feature Selection"><span class="progress-dot"></span>Feature Selection</a></li><li data-subkey="sec2sub4"><a href="/Model-Selection-in-R.html" title="Model Selection"><span class="progress-dot"></span>Model Selection</a></li><li data-subkey="sec2sub4"><a href="/Missing-Value-Treatment-With-R.html" title="Missing Value Treatment"><span class="progress-dot"></span>Missing Value Treatment</a></li><li data-subkey="sec2sub4"><a href="/Outlier-Treatment-With-R.html" title="Outlier Analysis"><span class="progress-dot"></span>Outlier Analysis</a></li><li data-subkey="sec2sub4"><a href="/adv-regression-models.html" title="Advanced Regression Models"><span class="progress-dot"></span>Advanced Regression Models</a></li><li data-subkey="sec2sub4" class="is-quiz"><a href="/Linear-Regression-Exercises-in-R-quiz.html" title="Linear Regression Quiz"><span class="quiz-marker" aria-hidden="true"><svg viewBox="0 0 24 24" fill="currentColor" aria-hidden="true"><path d="M12 2 4 5.1v5.7c0 4.9 3.4 8.4 8 9.9 4.6-1.5 8-5 8-9.9V5.1L12 2z"/></svg></span>Quiz</a></li><li class="sidebar-divider sidebar-subsection-toggle" data-subkey="sec2sub5" data-collapsed="false"><span class="subsec-chevron">▼</span> Reporting & Communication</li><li data-subkey="sec2sub5"><a href="/Statistical-Consulting-in-R.html" title="Statistical Consulting"><span class="progress-dot"></span>Statistical Consulting</a></li><li data-subkey="sec2sub5"><a href="/Statistical-Report-Writing-in-R.html" title="Statistical Report Writing"><span class="progress-dot"></span>Statistical Report Writing</a></li><li data-subkey="sec2sub5"><a href="/Bootstrap-Confidence-Intervals-in-R.html" title="Bootstrap Confidence Intervals"><span class="progress-dot"></span>Bootstrap Confidence Intervals</a></li><li data-subkey="sec2sub5"><a href="/Reporting-Statistics-in-R.html" title="Reporting Statistics"><span class="progress-dot"></span>Reporting Statistics</a></li><li data-subkey="sec2sub5"><a href="/Regression-Tables-in-R.html" title="Regression Tables (3 packages)"><span class="progress-dot"></span>Regression Tables (3 packages)</a></li><li class="sidebar-divider sidebar-subsection-toggle" data-subkey="sec2sub6" data-collapsed="false"><span class="subsec-chevron">▼</span> Regression in Practice</li><li data-subkey="sec2sub6"><a href="/Simple-Linear-Regression-in-R.html" title="Simple Linear Regression"><span class="progress-dot"></span>Simple Linear Regression</a></li><li data-subkey="sec2sub6"><a href="/Multiple-Regression-in-R.html" title="Multiple Regression"><span class="progress-dot"></span>Multiple Regression</a></li><li data-subkey="sec2sub6"><a href="/Correlation-in-R.html" title="Correlation (Pearson, Spearman, Kendall)"><span class="progress-dot"></span>Correlation (Pearson, Spearman, Kendall)</a></li><li data-subkey="sec2sub6"><a href="/Linear-Regression-Assumptions-in-R.html" title="Linear Regression Assumptions"><span class="progress-dot"></span>Linear Regression Assumptions</a></li><li data-subkey="sec2sub6"><a href="/Dummy-Variables-in-R.html" title="Dummy Variables in R"><span class="progress-dot"></span>Dummy Variables in R</a></li><li data-subkey="sec2sub6"><a href="/Interaction-Effects-in-R.html" title="Interaction Effects"><span class="progress-dot"></span>Interaction Effects</a></li><li data-subkey="sec2sub6"><a href="/Regression-Diagnostics-in-R.html" title="Regression Diagnostics"><span class="progress-dot"></span>Regression Diagnostics</a></li><li data-subkey="sec2sub6"><a href="/Variable-Selection-in-R.html" title="Variable Selection"><span class="progress-dot"></span>Variable Selection</a></li><li data-subkey="sec2sub6"><a href="/Polynomial-and-Spline-Regression-in-R.html" title="Polynomial & Splines"><span class="progress-dot"></span>Polynomial & Splines</a></li><li data-subkey="sec2sub6"><a href="/Ridge-and-Lasso-Regression-in-R.html" title="Ridge & Lasso Regression"><span class="progress-dot"></span>Ridge & Lasso Regression</a></li><li data-subkey="sec2sub6"><a href="/Robust-Regression-in-R.html" title="Robust Regression (rlm)"><span class="progress-dot"></span>Robust Regression (rlm)</a></li><li data-subkey="sec2sub6"><a href="/Quantile-Regression-in-R-2.html" title="Quantile Regression"><span class="progress-dot"></span>Quantile Regression</a></li><li class="sidebar-divider sidebar-subsection-toggle" data-subkey="sec2sub7" data-collapsed="false"><span class="subsec-chevron">▼</span> ANOVA & Experiments</li><li data-subkey="sec2sub7"><a href="/One-Way-ANOVA-in-R.html" title="One-Way ANOVA"><span class="progress-dot"></span>One-Way ANOVA</a></li><li data-subkey="sec2sub7"><a href="/Post-Hoc-Tests-After-ANOVA.html" title="Post-Hoc Tests After ANOVA"><span class="progress-dot"></span>Post-Hoc Tests After ANOVA</a></li><li data-subkey="sec2sub7"><a href="/Two-Way-ANOVA-in-R.html" title="Two-Way ANOVA"><span class="progress-dot"></span>Two-Way ANOVA</a></li><li data-subkey="sec2sub7"><a href="/Repeated-Measures-ANOVA-in-R.html" title="Repeated Measures ANOVA"><span class="progress-dot"></span>Repeated Measures ANOVA</a></li><li data-subkey="sec2sub7"><a href="/ANCOVA-in-R.html" title="ANCOVA"><span class="progress-dot"></span>ANCOVA</a></li><li data-subkey="sec2sub7"><a href="/Experimental-Design-Principles-in-R.html" title="Experimental Design in R"><span class="progress-dot"></span>Experimental Design in R</a></li><li data-subkey="sec2sub7"><a href="/Factorial-Experiments-in-R.html" title="Factorial Designs (2^k)"><span class="progress-dot"></span>Factorial Designs (2^k)</a></li><li data-subkey="sec2sub7"><a href="/AB-Testing-in-R.html" title="A/B Testing"><span class="progress-dot"></span>A/B Testing</a></li><li data-subkey="sec2sub7"><a href="/MANOVA-in-R.html" title="MANOVA"><span class="progress-dot"></span>MANOVA</a></li><li data-subkey="sec2sub7"><a href="/Mixed-ANOVA-in-R.html" title="Mixed ANOVA"><span class="progress-dot"></span>Mixed ANOVA</a></li><li class="sidebar-divider sidebar-subsection-toggle" data-subkey="sec2sub8" data-collapsed="false"><span class="subsec-chevron">▼</span> GLMs & Categorical Data</li><li data-subkey="sec2sub8"><a href="/Categorical-Data-in-R.html" title="Categorical Data (Tables & Mosaic)"><span class="progress-dot"></span>Categorical Data (Tables & Mosaic)</a></li><li data-subkey="sec2sub8"><a href="/Chi-Square-Test-of-Independence-in-R.html" title="Chi-Square Test of Independence"><span class="progress-dot"></span>Chi-Square Test of Independence</a></li><li data-subkey="sec2sub8"><a href="/Chi-Square-Goodness-of-Fit-Test-in-R.html" title="Chi-Square Goodness-of-Fit"><span class="progress-dot"></span>Chi-Square Goodness-of-Fit</a></li><li data-subkey="sec2sub8"><a href="/Fishers-Exact-Test-in-R.html" title="Fisher's Exact Test"><span class="progress-dot"></span>Fisher's Exact Test</a></li><li data-subkey="sec2sub8"><a href="/Odds-Ratios-and-Relative-Risk-in-R.html" title="Odds Ratios & Relative Risk"><span class="progress-dot"></span>Odds Ratios & Relative Risk</a></li><li data-subkey="sec2sub8"><a href="/Logistic-Regression-in-R.html" title="Logistic Regression (glm + ROC)"><span class="progress-dot"></span>Logistic Regression (glm + ROC)</a></li><li data-subkey="sec2sub8"><a href="/Logistic-Regression-in-R-2.html" title="Logistic Regression (Diagnostics)"><span class="progress-dot"></span>Logistic Regression (Diagnostics)</a></li><li data-subkey="sec2sub8"><a href="/Poisson-Regression-in-R.html" title="Poisson Regression"><span class="progress-dot"></span>Poisson Regression</a></li><li data-subkey="sec2sub8"><a href="/Poisson-and-Negative-Binomial-Regression.html" title="Poisson & Negative Binomial Regression"><span class="progress-dot"></span>Poisson & Negative Binomial Regression</a></li><li data-subkey="sec2sub8"><a href="/Multinomial-and-Ordinal-Logistic-Regression-in-R.html" title="Multinomial & Ordinal Logistic Regression"><span class="progress-dot"></span>Multinomial & Ordinal Logistic Regression</a></li><li class="sidebar-divider sidebar-subsection-toggle" data-subkey="sec2sub9" data-collapsed="false"><span class="subsec-chevron">▼</span> Multivariate Methods</li><li data-subkey="sec2sub9"><a href="/Multivariate-Statistics-in-R.html" title="Multivariate Distances & Hotelling's T²"><span class="progress-dot"></span>Multivariate Distances & Hotelling's T²</a></li><li data-subkey="sec2sub9"><a href="/PCA-in-R.html" title="PCA with prcomp()"><span class="progress-dot"></span>PCA with prcomp()</a></li><li data-subkey="sec2sub9"><a href="/Interpreting-PCA-Results-in-R.html" title="Interpreting PCA Output"><span class="progress-dot"></span>Interpreting PCA Output</a></li><li data-subkey="sec2sub9"><a href="/factoextra-and-FactoMineR.html" title="factoextra (PCA + Clusters)"><span class="progress-dot"></span>factoextra (PCA + Clusters)</a></li><li data-subkey="sec2sub9"><a href="/Exploratory-Factor-Analysis-in-R.html" title="Exploratory Factor Analysis"><span class="progress-dot"></span>Exploratory Factor Analysis</a></li><li data-subkey="sec2sub9"><a href="/CFA-and-Structural-Equation-Modeling-in-R.html" title="SEM and CFA (lavaan)"><span class="progress-dot"></span>SEM and CFA (lavaan)</a></li><li data-subkey="sec2sub9"><a href="/Linear-Discriminant-Analysis-in-R.html" title="LDA (Linear Discriminant Analysis)"><span class="progress-dot"></span>LDA (Linear Discriminant Analysis)</a></li><li data-subkey="sec2sub9"><a href="/Cluster-Analysis-in-R.html" title="Clustering (k-Means / HC / DBSCAN)"><span class="progress-dot"></span>Clustering (k-Means / HC / DBSCAN)</a></li><li data-subkey="sec2sub9"><a href="/Correspondence-Analysis-in-R.html" title="Correspondence Analysis"><span class="progress-dot"></span>Correspondence Analysis</a></li><li data-subkey="sec2sub9"><a href="/t-SNE-and-UMAP-in-R.html" title="t-SNE and UMAP"><span class="progress-dot"></span>t-SNE and UMAP</a></li><li class="sidebar-divider sidebar-subsection-toggle" data-subkey="sec2sub10" data-collapsed="false"><span class="subsec-chevron">▼</span> Nonparametric & Resampling</li><li data-subkey="sec2sub10"><a href="/When-to-Use-Nonparametric-Tests-in-R.html" title="When to Use Nonparametric Tests"><span class="progress-dot"></span>When to Use Nonparametric Tests</a></li><li data-subkey="sec2sub10"><a href="/Wilcoxon-Signed-Rank-Test-in-R.html" title="Wilcoxon Signed-Rank Test"><span class="progress-dot"></span>Wilcoxon Signed-Rank Test</a></li><li data-subkey="sec2sub10"><a href="/Mann-Whitney-U-Test-in-R.html" title="Mann-Whitney U Test"><span class="progress-dot"></span>Mann-Whitney U Test</a></li><li data-subkey="sec2sub10"><a href="/Kruskal-Wallis-Test-in-R-2.html" title="Kruskal-Wallis Test"><span class="progress-dot"></span>Kruskal-Wallis Test</a></li><li data-subkey="sec2sub10"><a href="/Friedman-Test-in-R.html" title="Friedman Test"><span class="progress-dot"></span>Friedman Test</a></li><li data-subkey="sec2sub10"><a href="/Spearman-and-Kendall-Correlation-in-R.html" title="Spearman & Kendall Correlation"><span class="progress-dot"></span>Spearman & Kendall Correlation</a></li><li data-subkey="sec2sub10"><a href="/Bootstrap-in-R.html" title="Bootstrap (boot package)"><span class="progress-dot"></span>Bootstrap (boot package)</a></li><li class="sidebar-divider sidebar-subsection-toggle" data-subkey="sec2sub11" data-collapsed="false"><span class="subsec-chevron">▼</span> Linear Algebra for Statistics</li><li data-subkey="sec2sub11"><a href="/Matrix-Operations-in-R.html" title="Matrix Operations in R"><span class="progress-dot"></span>Matrix Operations in R</a></li><li data-subkey="sec2sub11"><a href="/Solving-Linear-Systems-in-R.html" title="Solving Linear Systems in R"><span class="progress-dot"></span>Solving Linear Systems in R</a></li><li data-subkey="sec2sub11"><a href="/Eigenvalues-and-Eigenvectors-in-R.html" title="Eigenvalues & Eigenvectors in R"><span class="progress-dot"></span>Eigenvalues & Eigenvectors in R</a></li><li data-subkey="sec2sub11"><a href="/Singular-Value-Decomposition-in-R.html" title="Singular Value Decomposition in R"><span class="progress-dot"></span>Singular Value Decomposition in R</a></li><li data-subkey="sec2sub11"><a href="/Projections-and-the-Hat-Matrix-in-R.html" title="Projections & the Hat Matrix"><span class="progress-dot"></span>Projections & the Hat Matrix</a></li><li data-subkey="sec2sub11"><a href="/QR-Decomposition-in-R.html" title="QR Decomposition in R"><span class="progress-dot"></span>QR Decomposition in R</a></li><li data-subkey="sec2sub11"><a href="/Quadratic-Forms-in-R.html" title="Quadratic Forms"><span class="progress-dot"></span>Quadratic Forms</a></li><li data-subkey="sec2sub11"><a href="/Matrix-Derivatives-and-the-Hessian-in-R.html" title="Matrix Derivatives & Hessian"><span class="progress-dot"></span>Matrix Derivatives & Hessian</a></li><li class="sidebar-divider sidebar-subsection-toggle" data-subkey="sec2sub12" data-collapsed="false"><span class="subsec-chevron">▼</span> Statistical Theory</li><li data-subkey="sec2sub12"><a href="/Exponential-Family-Distributions-in-R.html" title="Exponential Family Distributions"><span class="progress-dot"></span>Exponential Family Distributions</a></li><li data-subkey="sec2sub12"><a href="/Sufficient-Statistics-in-R.html" title="Sufficient Statistics"><span class="progress-dot"></span>Sufficient Statistics</a></li><li data-subkey="sec2sub12"><a href="/Complete-and-Ancillary-Statistics-in-R.html" title="Complete & Ancillary Statistics"><span class="progress-dot"></span>Complete & Ancillary Statistics</a></li><li data-subkey="sec2sub12"><a href="/UMVUE-in-R-2.html" title="UMVUE (Rao-Blackwell & Lehmann-Scheffé)"><span class="progress-dot"></span>UMVUE (Rao-Blackwell & Lehmann-Scheffé)</a></li><li data-subkey="sec2sub12"><a href="/Cramer-Rao-Lower-Bound-in-R-2.html" title="Cramér-Rao Lower Bound"><span class="progress-dot"></span>Cramér-Rao Lower Bound</a></li><li data-subkey="sec2sub12"><a href="/Asymptotic-Theory-in-R-2.html" title="Asymptotic Theory"><span class="progress-dot"></span>Asymptotic Theory</a></li><li data-subkey="sec2sub12"><a href="/Neyman-Pearson-Lemma-in-R-2.html" title="Neyman-Pearson Lemma"><span class="progress-dot"></span>Neyman-Pearson Lemma</a></li><li data-subkey="sec2sub12"><a href="/Likelihood-Ratio-Tests-and-Pivotal-Methods.html" title="Likelihood Ratio & Pivotal Methods"><span class="progress-dot"></span>Likelihood Ratio & Pivotal Methods</a></li><li data-subkey="sec2sub12"><a href="/Decision-Theory-in-R.html" title="Decision Theory"><span class="progress-dot"></span>Decision Theory</a></li><li data-subkey="sec2sub12"><a href="/Asymptotic-Relative-Efficiency-in-R.html" title="Asymptotic Relative Efficiency"><span class="progress-dot"></span>Asymptotic Relative Efficiency</a></li><li class="sidebar-divider sidebar-subsection-toggle" data-subkey="sec2sub13" data-collapsed="false"><span class="subsec-chevron">▼</span> Bayesian Foundations</li><li data-subkey="sec2sub13"><a href="/Bayes-Theorem-in-R.html" title="Bayes' Theorem"><span class="progress-dot"></span>Bayes' Theorem</a></li><li data-subkey="sec2sub13"><a href="/Bayesian-Statistics-in-R.html" title="Bayesian Statistics"><span class="progress-dot"></span>Bayesian Statistics</a></li><li data-subkey="sec2sub13"><a href="/Conjugate-Priors-in-R.html" title="Conjugate Priors"><span class="progress-dot"></span>Conjugate Priors</a></li><li data-subkey="sec2sub13"><a href="/Grid-Approximation-in-R.html" title="Grid Approximation"><span class="progress-dot"></span>Grid Approximation</a></li><li class="sidebar-divider sidebar-subsection-toggle" data-subkey="sec2sub14" data-collapsed="false"><span class="subsec-chevron">▼</span> MCMC & Stan</li><li data-subkey="sec2sub14"><a href="/MCMC-in-R.html" title="MCMC in R"><span class="progress-dot"></span>MCMC in R</a></li><li data-subkey="sec2sub14"><a href="/Gibbs-Sampling-in-R.html" title="Gibbs Sampling"><span class="progress-dot"></span>Gibbs Sampling</a></li><li data-subkey="sec2sub14"><a href="/Hamiltonian-Monte-Carlo-in-R.html" title="Hamiltonian Monte Carlo"><span class="progress-dot"></span>Hamiltonian Monte Carlo</a></li><li data-subkey="sec2sub14"><a href="/Stan-in-R.html" title="Stan"><span class="progress-dot"></span>Stan</a></li><li data-subkey="sec2sub14"><a href="/brms-in-R.html" title="brms"><span class="progress-dot"></span>brms</a></li><li class="sidebar-divider sidebar-subsection-toggle" data-subkey="sec2sub15" data-collapsed="false"><span class="subsec-chevron">▼</span> Bayesian Modeling</li><li data-subkey="sec2sub15"><a href="/Choosing-Priors-in-R.html" title="Choosing Priors"><span class="progress-dot"></span>Choosing Priors</a></li><li data-subkey="sec2sub15"><a href="/Prior-Predictive-Checks-in-R.html" title="Prior Predictive Checks"><span class="progress-dot"></span>Prior Predictive Checks</a></li><li data-subkey="sec2sub15"><a href="/Compare-Bayesian-Models-in-R.html" title="Compare Bayesian Models"><span class="progress-dot"></span>Compare Bayesian Models</a></li><li data-subkey="sec2sub15"><a href="/Posterior-Predictive-Checks-in-R.html" title="Posterior Predictive Checks"><span class="progress-dot"></span>Posterior Predictive Checks</a></li><li data-subkey="sec2sub15"><a href="/Bayesian-Linear-Regression-in-R.html" title="Bayesian Linear Regression"><span class="progress-dot"></span>Bayesian Linear Regression</a></li><li data-subkey="sec2sub15"><a href="/Bayesian-Logistic-Regression-in-R.html" title="Bayesian Logistic Regression"><span class="progress-dot"></span>Bayesian Logistic Regression</a></li><li data-subkey="sec2sub15"><a href="/Bayesian-Hierarchical-Models-in-R.html" title="Bayesian Hierarchical Models"><span class="progress-dot"></span>Bayesian Hierarchical Models</a></li><li data-subkey="sec2sub15"><a href="/Multilevel-Models-in-R.html" title="Multilevel Models"><span class="progress-dot"></span>Multilevel Models</a></li><li data-subkey="sec2sub15"><a href="/Bayesian-ANOVA-in-R.html" title="Bayesian ANOVA"><span class="progress-dot"></span>Bayesian ANOVA</a></li><li class="sidebar-divider sidebar-subsection-toggle" data-subkey="sec2sub16" data-collapsed="false"><span class="subsec-chevron">▼</span> Machine Learning</li><li data-subkey="sec2sub16"><a href="/Random-Forest-Course.html" title="Random Forests (Course)"><span class="progress-dot"></span>Random Forests (Course)</a></li><li data-subkey="sec2sub16"><a href="/R-Gradient-Boosting-Course.html" title="Gradient Boosting (Course)"><span class="progress-dot"></span>Gradient Boosting (Course)</a></li><li data-subkey="sec2sub16"><a href="/R-tidymodels-Course.html" title="tidymodels (Course)"><span class="progress-dot"></span>tidymodels (Course)</a></li><li data-subkey="sec2sub16" class="is-quiz"><a href="/Machine-Learning-Exercises-in-R-quiz.html" title="Machine Learning Quiz"><span class="quiz-marker" aria-hidden="true"><svg viewBox="0 0 24 24" fill="currentColor" aria-hidden="true"><path d="M12 2 4 5.1v5.7c0 4.9 3.4 8.4 8 9.9 4.6-1.5 8-5 8-9.9V5.1L12 2z"/></svg></span>Quiz</a></li><li data-subkey="sec2sub16"><a href="/T-Test-Course.html" title="The t-test (Lesson)"><span class="progress-dot"></span>The t-test (Lesson)</a></li><li data-subkey="sec2sub16"><a href="/Populations-Samples-and-Bias-in-R.html" title="Populations & Sampling Bias"><span class="progress-dot"></span>Populations & Sampling Bias</a></li><li data-subkey="sec2sub16"><a href="/Types-of-Data-in-Statistics.html" title="Types of Data"><span class="progress-dot"></span>Types of Data</a></li><li data-subkey="sec2sub16"><a href="/What-Statistics-Is-For.html" title="What Statistics Is For"><span class="progress-dot"></span>What Statistics Is For</a></li><li data-subkey="sec2sub16"><a href="/Mean-vs-Median-SD-vs-IQR.html" title="Mean, Median, SD & IQR"><span class="progress-dot"></span>Mean, Median, SD & IQR</a></li><li data-subkey="sec2sub16"><a href="/Sampling-Methods-in-R.html" title="Sampling Methods"><span class="progress-dot"></span>Sampling Methods</a></li><li data-subkey="sec2sub16"><a href="/Z-Scores-and-Percentiles-in-R.html" title="Z-Scores & Percentiles"><span class="progress-dot"></span>Z-Scores & Percentiles</a></li><li data-subkey="sec2sub16"><a href="/Covariance-and-Correlation-in-R.html" title="Covariance & Correlation"><span class="progress-dot"></span>Covariance & Correlation</a></li><li data-subkey="sec2sub16"><a href="/The-Normal-Distribution-Explained-in-R.html" title="Normal Distribution"><span class="progress-dot"></span>Normal Distribution</a></li><li data-subkey="sec2sub16"><a href="/Which-Distribution-When-in-R.html" title="Which Distribution When"><span class="progress-dot"></span>Which Distribution When</a></li><li data-subkey="sec2sub16"><a href="/First-Hypothesis-Test-Three-Ways-in-R.html" title="First Hypothesis Test"><span class="progress-dot"></span>First Hypothesis Test</a></li><li data-subkey="sec2sub16"><a href="/How-Statistical-Inference-Works.html" title="How Inference Works"><span class="progress-dot"></span>How Inference Works</a></li><li data-subkey="sec2sub16"><a href="/Margin-of-Error-in-R.html" title="Margin of Error & Sample Size"><span class="progress-dot"></span>Margin of Error & Sample Size</a></li><li data-subkey="sec2sub16"><a href="/Paired-Designs-in-R.html" title="Paired Designs"><span class="progress-dot"></span>Paired Designs</a></li><li data-subkey="sec2sub16"><a href="/Statistical-vs-Practical-Significance.html" title="Statistical vs Practical"><span class="progress-dot"></span>Statistical vs Practical</a></li><li data-subkey="sec2sub16"><a href="/What-p-Values-Mean.html" title="What p-Values Mean"><span class="progress-dot"></span>What p-Values Mean</a></li><li data-subkey="sec2sub16"><a href="/Power-by-Simulation-in-R.html" title="Power by Simulation"><span class="progress-dot"></span>Power by Simulation</a></li><li data-subkey="sec2sub16"><a href="/Read-Logistic-Output-in-R.html" title="Reading glm() Output"><span class="progress-dot"></span>Reading glm() Output</a></li><li data-subkey="sec2sub16"><a href="/Read-lm-Output-in-R.html" title="Reading lm() Output"><span class="progress-dot"></span>Reading lm() Output</a></li><li data-subkey="sec2sub16"><a href="/Offsets-and-Exposure-in-R.html" title="Offsets & Exposure"><span class="progress-dot"></span>Offsets & Exposure</a></li><li data-subkey="sec2sub16"><a href="/Zero-Inflated-Hurdle-Models-in-R.html" title="Zero-Inflated & Hurdle Models"><span class="progress-dot"></span>Zero-Inflated & Hurdle Models</a></li><li data-subkey="sec2sub16"><a href="/GLM-Diagnostics-in-R.html" title="GLM Diagnostics"><span class="progress-dot"></span>GLM Diagnostics</a></li><li data-subkey="sec2sub16"><a href="/Random-Intercepts-and-Slopes-in-R.html" title="Random Intercepts & Slopes"><span class="progress-dot"></span>Random Intercepts & Slopes</a></li><li data-subkey="sec2sub16"><a href="/Checking-Assumptions-in-R.html" title="Checking Model Assumptions"><span class="progress-dot"></span>Checking Model Assumptions</a></li><li data-subkey="sec2sub16"><a href="/Crossed-vs-Nested-Effects-in-R.html" title="Crossed vs Nested Effects"><span class="progress-dot"></span>Crossed vs Nested Effects</a></li><li data-subkey="sec2sub16"><a href="/GEE-vs-Mixed-Models-in-R.html" title="GEE vs Mixed Models"><span class="progress-dot"></span>GEE vs Mixed Models</a></li><li data-subkey="sec2sub16"><a href="/Mixed-Model-Inference-in-R.html" title="Mixed Model Inference"><span class="progress-dot"></span>Mixed Model Inference</a></li><li data-subkey="sec2sub16"><a href="/Measurement-Reliability-in-R.html" title="Measurement Reliability"><span class="progress-dot"></span>Measurement Reliability</a></li><li data-subkey="sec2sub16"><a href="/Multiple-Imputation-mice-in-R.html" title="Multiple Imputation with mice"><span class="progress-dot"></span>Multiple Imputation with mice</a></li><li data-subkey="sec2sub16"><a href="/p-Hacking-and-Preregistration.html" title="p-Hacking and Preregistration"><span class="progress-dot"></span>p-Hacking and Preregistration</a></li><li data-subkey="sec2sub16"><a href="/Business-Experiment-Capstone-in-R.html" title="Business Experiment Capstone"><span class="progress-dot"></span>Business Experiment Capstone</a></li><li data-subkey="sec2sub16"><a href="/Clinical-Comparison-Capstone-in-R.html" title="Clinical Comparison Capstone"><span class="progress-dot"></span>Clinical Comparison Capstone</a></li><li data-subkey="sec2sub16"><a href="/Survey-Analysis-Capstone-in-R.html" title="Survey Analysis Capstone"><span class="progress-dot"></span>Survey Analysis Capstone</a></li><li data-subkey="sec2sub16"><a href="/Bayesian-Workflow-in-R.html" title="Bayesian Workflow"><span class="progress-dot"></span>Bayesian Workflow</a></li><li data-subkey="sec2sub16"><a href="/MCMC-Diagnostics-in-R.html" title="MCMC Diagnostics"><span class="progress-dot"></span>MCMC Diagnostics</a></li><li data-subkey="sec2sub16"><a href="/Answering-Statistical-Reviewer-Comments.html" title="Answering Reviewer Comments"><span class="progress-dot"></span>Answering Reviewer Comments</a></li></ul></li><li class="sidebar-section expanded"><div class="sidebar-section-header"><span class="sidebar-chevron">▸</span><span class="sec-num">4.</span> <span class="sec-title-t">Visualization</span><span class="section-meta" data-section-meta></span></div><ul class="sidebar-section-items list-unstyled"><li class="sidebar-divider sidebar-subsection-toggle" data-subkey="sec3sub1" data-collapsed="false"><span class="subsec-chevron">▼</span> ggplot2 Foundations</li><li data-subkey="sec3sub1"><a href="/ggplot2-Grammar-of-Graphics.html" title="Grammar of Graphics"><span class="progress-dot"></span>Grammar of Graphics</a></li><li data-subkey="sec3sub1"><a href="/ggplot2-Getting-Started.html" title="ggplot2 Getting Started"><span class="progress-dot"></span>ggplot2 Getting Started</a></li><li data-subkey="sec3sub1"><a href="/ggplot2-Aesthetics-aes-Map-Data.html" title="ggplot2 Aesthetics (aes)"><span class="progress-dot"></span>ggplot2 Aesthetics (aes)</a></li><li data-subkey="sec3sub1"><a href="/ggplot2-Colours.html" title="ggplot2 Colours"><span class="progress-dot"></span>ggplot2 Colours</a></li><li data-subkey="sec3sub1"><a href="/ggplot2-Scales.html" title="ggplot2 Scales"><span class="progress-dot"></span>ggplot2 Scales</a></li><li data-subkey="sec3sub1"><a href="/ggplot2-Themes-in-R.html" title="ggplot2 Themes"><span class="progress-dot"></span>ggplot2 Themes</a></li><li data-subkey="sec3sub1"><a href="/ggplot2-Labels-and-Annotations.html" title="Labels & Annotations"><span class="progress-dot"></span>Labels & Annotations</a></li><li data-subkey="sec3sub1"><a href="/ggplot2-Facets.html" title="ggplot2 Facets"><span class="progress-dot"></span>ggplot2 Facets</a></li><li data-subkey="sec3sub1" class="is-quiz"><a href="/ggplot2-Exercises-in-R-quiz.html" title="ggplot2 Quiz"><span class="quiz-marker" aria-hidden="true"><svg viewBox="0 0 24 24" fill="currentColor" aria-hidden="true"><path d="M12 2 4 5.1v5.7c0 4.9 3.4 8.4 8 9.9 4.6-1.5 8-5 8-9.9V5.1L12 2z"/></svg></span>Quiz</a></li><li class="sidebar-divider sidebar-subsection-toggle" data-subkey="sec3sub2" data-collapsed="false"><span class="subsec-chevron">▼</span> Core Charts</li><li data-subkey="sec3sub2"><a href="/ggplot2-Scatter-Plots.html" title="Scatter Plots"><span class="progress-dot"></span>Scatter Plots</a></li><li data-subkey="sec3sub2"><a href="/ggplot2-Line-Charts.html" title="Line Charts"><span class="progress-dot"></span>Line Charts</a></li><li data-subkey="sec3sub2"><a href="/ggplot2-Bar-Charts.html" title="Bar Charts"><span class="progress-dot"></span>Bar Charts</a></li><li data-subkey="sec3sub2"><a href="/ggplot2-Distribution-Charts.html" title="Distribution Charts"><span class="progress-dot"></span>Distribution Charts</a></li><li data-subkey="sec3sub2"><a href="/Error-Bars-in-R.html" title="Error Bars"><span class="progress-dot"></span>Error Bars</a></li><li data-subkey="sec3sub2"><a href="/geom_smooth-in-R.html" title="geom_smooth()"><span class="progress-dot"></span>geom_smooth()</a></li><li class="sidebar-divider sidebar-subsection-toggle" data-subkey="sec3sub3" data-collapsed="false"><span class="subsec-chevron">▼</span> Distributions & Groups</li><li data-subkey="sec3sub3"><a href="/Violin-Plot-in-R.html" title="Violin Plot"><span class="progress-dot"></span>Violin Plot</a></li><li data-subkey="sec3sub3"><a href="/Ridgeline-Plot-in-R.html" title="Ridgeline Plot"><span class="progress-dot"></span>Ridgeline Plot</a></li><li data-subkey="sec3sub3"><a href="/Lollipop-Chart-in-R.html" title="Lollipop Chart"><span class="progress-dot"></span>Lollipop Chart</a></li><li class="sidebar-divider sidebar-subsection-toggle" data-subkey="sec3sub4" data-collapsed="false"><span class="subsec-chevron">▼</span> Relationships</li><li data-subkey="sec3sub4"><a href="/Bubble-Chart-in-R.html" title="Bubble Chart"><span class="progress-dot"></span>Bubble Chart</a></li><li data-subkey="sec3sub4"><a href="/Heatmap-in-R.html" title="Heatmap in R"><span class="progress-dot"></span>Heatmap in R</a></li><li data-subkey="sec3sub4"><a href="/Correlation-Matrix-Plot-in-R.html" title="Correlation Matrix"><span class="progress-dot"></span>Correlation Matrix</a></li><li class="sidebar-divider sidebar-subsection-toggle" data-subkey="sec3sub5" data-collapsed="false"><span class="subsec-chevron">▼</span> Advanced Charts</li><li data-subkey="sec3sub5"><a href="/Pie-Donut-Chart-in-R.html" title="Pie & Donut Chart"><span class="progress-dot"></span>Pie & Donut Chart</a></li><li data-subkey="sec3sub5"><a href="/Treemap-in-R.html" title="Treemap"><span class="progress-dot"></span>Treemap</a></li><li data-subkey="sec3sub5"><a href="/Waffle-Chart-in-R.html" title="Waffle Chart"><span class="progress-dot"></span>Waffle Chart</a></li><li class="sidebar-divider sidebar-subsection-toggle" data-subkey="sec3sub6" data-collapsed="false"><span class="subsec-chevron">▼</span> Exploratory Analysis</li><li data-subkey="sec3sub6"><a href="/Exploratory-Data-Analysis-in-R.html" title="EDA (7-Step Framework)"><span class="progress-dot"></span>EDA (7-Step Framework)</a></li><li data-subkey="sec3sub6"><a href="/Univariate-EDA-in-R.html" title="Univariate EDA"><span class="progress-dot"></span>Univariate EDA</a></li><li data-subkey="sec3sub6"><a href="/Bivariate-EDA-in-R.html" title="Bivariate EDA"><span class="progress-dot"></span>Bivariate EDA</a></li><li data-subkey="sec3sub6"><a href="/Descriptive-Statistics-in-R.html" title="Descriptive Statistics"><span class="progress-dot"></span>Descriptive Statistics</a></li><li data-subkey="sec3sub6"><a href="/Correlation-Analysis-in-R.html" title="Correlation Analysis"><span class="progress-dot"></span>Correlation Analysis</a></li><li class="sidebar-divider sidebar-subsection-toggle" data-subkey="sec3sub7" data-collapsed="false"><span class="subsec-chevron">▼</span> Interactive & Maps</li><li data-subkey="sec3sub7"><a href="/Combining-ggplot2-with-plotly.html" title="ggplot2 + plotly Interactive"><span class="progress-dot"></span>ggplot2 + plotly Interactive</a></li><li data-subkey="sec3sub7"><a href="/Interactive-Maps-in-R-with-leaflet.html" title="Leaflet Interactive Maps"><span class="progress-dot"></span>Leaflet Interactive Maps</a></li><li data-subkey="sec3sub7"><a href="/Spatial-Data-in-R-with-sf.html" title="Spatial Data (sf)"><span class="progress-dot"></span>Spatial Data (sf)</a></li><li data-subkey="sec3sub7"><a href="/Choropleth-Maps-in-R.html" title="Choropleth Maps (sf)"><span class="progress-dot"></span>Choropleth Maps (sf)</a></li><li class="sidebar-divider sidebar-subsection-toggle" data-subkey="sec3sub8" data-collapsed="false"><span class="subsec-chevron">▼</span> Customization & Reference</li><li data-subkey="sec3sub8"><a href="/ggplot2-Legends-in-R.html" title="ggplot2 Legends"><span class="progress-dot"></span>ggplot2 Legends</a></li><li data-subkey="sec3sub8"><a href="/ggplot2-Secondary-Axis.html" title="Secondary Axis"><span class="progress-dot"></span>Secondary Axis</a></li><li data-subkey="sec3sub8"><a href="/ggplot2-Log-Scale.html" title="Log Scale"><span class="progress-dot"></span>Log Scale</a></li><li data-subkey="sec3sub8"><a href="/patchwork-Package.html" title="patchwork (Combine Plots)"><span class="progress-dot"></span>patchwork (Combine Plots)</a></li><li data-subkey="sec3sub8"><a href="/Publication-Quality-Figures-in-R.html" title="Publication-Ready Figures"><span class="progress-dot"></span>Publication-Ready Figures</a></li><li data-subkey="sec3sub8"><a href="/ggplot2-cheatsheet.html" title="ggplot2 Quickref"><span class="progress-dot"></span>ggplot2 Quickref</a></li><li data-subkey="sec3sub8"><a href="/Advanced-ggplot2-Course.html" title="Advanced ggplot2 (Course)"><span class="progress-dot"></span>Advanced ggplot2 (Course)</a></li><li data-subkey="sec3sub8"><a href="/ggplot2-Course.html" title="ggplot2 (Course)"><span class="progress-dot"></span>ggplot2 (Course)</a></li><li data-subkey="sec3sub8"><a href="/Dashboards-Course.html" title="Interactive Dashboards (Course)"><span class="progress-dot"></span>Interactive Dashboards (Course)</a></li><li data-subkey="sec3sub8"><a href="/Reading-ggplot2-Code-in-R.html" title="Reading ggplot2 Code"><span class="progress-dot"></span>Reading ggplot2 Code</a></li><li data-subkey="sec3sub8"><a href="/ggplot2-Area-Charts-and-Ribbons-in-R.html" title="Area Charts & Ribbons"><span class="progress-dot"></span>Area Charts & Ribbons</a></li><li data-subkey="sec3sub8"><a href="/ggplot2-Text-Labels-in-R.html" title="Text Labels in ggplot2"><span class="progress-dot"></span>Text Labels in ggplot2</a></li><li data-subkey="sec3sub8"><a href="/ggplot2-2D-Density-and-Hexbin-in-R.html" title="2D Density & Hexbin"><span class="progress-dot"></span>2D Density & Hexbin</a></li><li data-subkey="sec3sub8"><a href="/ggplot2-Error-Bars-in-R.html" title="Error Bars"><span class="progress-dot"></span>Error Bars</a></li><li data-subkey="sec3sub8"><a href="/ggplot2-Stat-System-in-R.html" title="The stat System"><span class="progress-dot"></span>The stat System</a></li><li data-subkey="sec3sub8"><a href="/Summary-Statistics-on-Plots-in-R.html" title="Summary Stats on Plots"><span class="progress-dot"></span>Summary Stats on Plots</a></li><li data-subkey="sec3sub8"><a href="/ggplot2-Date-Axis-in-R.html" title="Date & Time Axes"><span class="progress-dot"></span>Date & Time Axes</a></li><li data-subkey="sec3sub8"><a href="/ggplot2-Position-Adjustments-in-R.html" title="Position Adjustments"><span class="progress-dot"></span>Position Adjustments</a></li><li data-subkey="sec3sub8"><a href="/Statistical-Significance-on-Plots-in-R.html" title="Significance Brackets"><span class="progress-dot"></span>Significance Brackets</a></li><li data-subkey="sec3sub8"><a href="/Visualizing-Uncertainty-in-R.html" title="Visualizing Uncertainty"><span class="progress-dot"></span>Visualizing Uncertainty</a></li><li data-subkey="sec3sub8"><a href="/ggplot2-Scale-Transformations-in-R.html" title="Scale Transformations"><span class="progress-dot"></span>Scale Transformations</a></li><li data-subkey="sec3sub8"><a href="/Coefficient-Plots-and-Marginal-Effects-in-R.html" title="Coefficient Plots"><span class="progress-dot"></span>Coefficient Plots</a></li><li data-subkey="sec3sub8"><a href="/Custom-Fonts-in-R-Plots.html" title="Custom Fonts in Plots"><span class="progress-dot"></span>Custom Fonts in Plots</a></li><li data-subkey="sec3sub8"><a href="/Raincloud-Plots-in-R.html" title="Raincloud Plots"><span class="progress-dot"></span>Raincloud Plots</a></li><li data-subkey="sec3sub8"><a href="/Build-a-ggplot2-Theme-in-R.html" title="Build a ggplot2 Theme"><span class="progress-dot"></span>Build a ggplot2 Theme</a></li><li data-subkey="sec3sub8"><a href="/Chart-Annotation-Techniques-in-R.html" title="Chart Annotation"><span class="progress-dot"></span>Chart Annotation</a></li><li data-subkey="sec3sub8"><a href="/ggplot2-Extensions-in-R.html" title="ggplot2 Extensions"><span class="progress-dot"></span>ggplot2 Extensions</a></li><li data-subkey="sec3sub8"><a href="/Plot-Templates-and-Functions-in-R.html" title="Plot Template Functions"><span class="progress-dot"></span>Plot Template Functions</a></li><li data-subkey="sec3sub8"><a href="/Plotting-Big-Data-in-R.html" title="Plotting Big Data"><span class="progress-dot"></span>Plotting Big Data</a></li><li data-subkey="sec3sub8"><a href="/Write-a-ggplot2-Extension-in-R.html" title="Write a Geom & Stat"><span class="progress-dot"></span>Write a Geom & Stat</a></li><li data-subkey="sec3sub8"><a href="/Bump-Charts-in-R.html" title="Bump Charts"><span class="progress-dot"></span>Bump Charts</a></li><li data-subkey="sec3sub8"><a href="/Dumbbell-and-Slope-Charts-in-R.html" title="Dumbbell & Slope Charts"><span class="progress-dot"></span>Dumbbell & Slope Charts</a></li><li data-subkey="sec3sub8"><a href="/Population-Pyramids-and-Diverging-Bars-in-R.html" title="Population Pyramids"><span class="progress-dot"></span>Population Pyramids</a></li><li data-subkey="sec3sub8"><a href="/Bubble-Maps-in-R.html" title="Bubble & Point Maps"><span class="progress-dot"></span>Bubble & Point Maps</a></li><li data-subkey="sec3sub8"><a href="/Pie-Charts-and-Polar-Coordinates-in-R.html" title="Pie Charts and Polar Coords"><span class="progress-dot"></span>Pie Charts and Polar Coords</a></li><li data-subkey="sec3sub8"><a href="/Multi-Panel-Figures-in-R.html" title="Multi-Panel Figures"><span class="progress-dot"></span>Multi-Panel Figures</a></li><li data-subkey="sec3sub8"><a href="/Small-Multiples-in-R.html" title="Small Multiples"><span class="progress-dot"></span>Small Multiples</a></li><li data-subkey="sec3sub8"><a href="/ggplot2-Inset-Plots-in-R.html" title="Inset & Magnifier Plots"><span class="progress-dot"></span>Inset & Magnifier Plots</a></li><li data-subkey="sec3sub8"><a href="/Export-Plots-in-R.html" title="Export & Save Plots"><span class="progress-dot"></span>Export & Save Plots</a></li><li data-subkey="sec3sub8"><a href="/gganimate-in-R.html" title="gganimate"><span class="progress-dot"></span>gganimate</a></li><li data-subkey="sec3sub8"><a href="/ggiraph-Interactive-Charts-in-R.html" title="ggiraph: Interactive Charts"><span class="progress-dot"></span>ggiraph: Interactive Charts</a></li><li data-subkey="sec3sub8"><a href="/Accessible-Data-Visualization-in-R.html" class="active" title="Accessible Charts"><span class="progress-dot"></span>Accessible Charts</a></li><li data-subkey="sec3sub8"><a href="/Publication-Figure-System-in-R.html" title="Publication Figure System"><span class="progress-dot"></span>Publication Figure System</a></li><li data-subkey="sec3sub8"><a href="/Recreating-Professional-Charts-in-R.html" title="Recreating Pro Charts"><span class="progress-dot"></span>Recreating Pro Charts</a></li><li data-subkey="sec3sub8"><a href="/Advanced-Faceting-in-R.html" title="Advanced Faceting"><span class="progress-dot"></span>Advanced Faceting</a></li></ul></li><li class="sidebar-section"><div class="sidebar-section-header"><span class="sidebar-chevron">▸</span><span class="sec-num">5.</span> <span class="sec-title-t">Time Series</span><span class="section-meta" data-section-meta></span></div><ul class="sidebar-section-items list-unstyled"><li data-subkey="sec4sub0"><a href="/Time-Series-Analysis-With-R.html" title="Time Series Analysis"><span class="progress-dot"></span>Time Series Analysis</a></li><li data-subkey="sec4sub0"><a href="/Time-Series-Forecasting-With-R.html" title="Time Series Forecasting"><span class="progress-dot"></span>Time Series Forecasting</a></li><li data-subkey="sec4sub0"><a href="/Time-Series-Forecasting-With-R-part2.html" title="More Time Series Forecasting"><span class="progress-dot"></span>More Time Series Forecasting</a></li><li data-subkey="sec4sub0" class="is-quiz"><a href="/Time-Series-Exercises-in-R-quiz.html" title="Time Series Quiz"><span class="quiz-marker" aria-hidden="true"><svg viewBox="0 0 24 24" fill="currentColor" aria-hidden="true"><path d="M12 2 4 5.1v5.7c0 4.9 3.4 8.4 8 9.9 4.6-1.5 8-5 8-9.9V5.1L12 2z"/></svg></span>Quiz</a></li><li data-subkey="sec4sub0"><a href="/Test-Stationarity-in-R.html" title="Test Stationarity"><span class="progress-dot"></span>Test Stationarity</a></li><li data-subkey="sec4sub0"><a href="/Time-Series-Objects-in-R.html" title="Time Series Objects"><span class="progress-dot"></span>Time Series Objects</a></li><li data-subkey="sec4sub0"><a href="/Visualize-Time-Series-in-R.html" title="Visualize Time Series"><span class="progress-dot"></span>Visualize Time Series</a></li><li data-subkey="sec4sub0"><a href="/ACF-and-PACF-in-R.html" title="ACF and PACF"><span class="progress-dot"></span>ACF and PACF</a></li><li data-subkey="sec4sub0"><a href="/Moving-Averages-in-R.html" title="Moving Averages"><span class="progress-dot"></span>Moving Averages</a></li><li data-subkey="sec4sub0"><a href="/Time-Series-Decomposition-in-R.html" title="Time Series Decomposition"><span class="progress-dot"></span>Time Series Decomposition</a></li><li data-subkey="sec4sub0"><a href="/ETS-Models-in-R.html" title="ETS Models"><span class="progress-dot"></span>ETS Models</a></li><li data-subkey="sec4sub0"><a href="/Exponential-Smoothing-in-R.html" title="Exponential Smoothing"><span class="progress-dot"></span>Exponential Smoothing</a></li><li data-subkey="sec4sub0"><a href="/Holt-Winters-in-R.html" title="Holt-Winters"><span class="progress-dot"></span>Holt-Winters</a></li><li data-subkey="sec4sub0"><a href="/ARIMA-Diagnostics-in-R.html" title="ARIMA Diagnostics"><span class="progress-dot"></span>ARIMA Diagnostics</a></li><li data-subkey="sec4sub0"><a href="/ARIMA-in-R.html" title="ARIMA Models"><span class="progress-dot"></span>ARIMA Models</a></li><li data-subkey="sec4sub0"><a href="/How-to-Choose-ARIMA-Order-in-R.html" title="Choose ARIMA Order"><span class="progress-dot"></span>Choose ARIMA Order</a></li><li data-subkey="sec4sub0"><a href="/SARIMA-in-R.html" title="SARIMA Models"><span class="progress-dot"></span>SARIMA Models</a></li><li data-subkey="sec4sub0"><a href="/auto-arima-in-R.html" title="auto.arima()"><span class="progress-dot"></span>auto.arima()</a></li><li data-subkey="sec4sub0"><a href="/Forecast-Accuracy-in-R.html" title="Forecast Accuracy"><span class="progress-dot"></span>Forecast Accuracy</a></li><li data-subkey="sec4sub0"><a href="/Time-Series-Cross-Validation-in-R.html" title="Time Series Cross-Validation"><span class="progress-dot"></span>Time Series Cross-Validation</a></li><li data-subkey="sec4sub0"><a href="/NNETAR-Model-in-R.html" title="NNETAR Models"><span class="progress-dot"></span>NNETAR Models</a></li><li data-subkey="sec4sub0"><a href="/Prophet-in-R.html" title="Prophet"><span class="progress-dot"></span>Prophet</a></li><li data-subkey="sec4sub0"><a href="/TBATS-Model-in-R.html" title="TBATS Model"><span class="progress-dot"></span>TBATS Model</a></li><li data-subkey="sec4sub0"><a href="/fable-in-R.html" title="fable and tsibble"><span class="progress-dot"></span>fable and tsibble</a></li><li data-subkey="sec4sub0"><a href="/GARCH-Models-in-R.html" title="GARCH Models"><span class="progress-dot"></span>GARCH Models</a></li><li data-subkey="sec4sub0"><a href="/Prediction-Intervals-in-R.html" title="Prediction Intervals"><span class="progress-dot"></span>Prediction Intervals</a></li><li data-subkey="sec4sub0"><a href="/VAR-Models-in-R.html" title="VAR Models"><span class="progress-dot"></span>VAR Models</a></li><li data-subkey="sec4sub0"><a href="/Anomaly-Detection-in-Time-Series-in-R.html" title="Anomaly Detection"><span class="progress-dot"></span>Anomaly Detection</a></li><li data-subkey="sec4sub0"><a href="/Changepoint-Detection-in-R.html" title="Changepoint Detection"><span class="progress-dot"></span>Changepoint Detection</a></li><li data-subkey="sec4sub0"><a href="/Combining-Forecasts-in-R.html" title="Combining Forecasts"><span class="progress-dot"></span>Combining Forecasts</a></li><li data-subkey="sec4sub0"><a href="/Cointegration-in-R.html" title="Cointegration"><span class="progress-dot"></span>Cointegration</a></li><li data-subkey="sec4sub0"><a href="/Kalman-Filter-in-R.html" title="Kalman Filter"><span class="progress-dot"></span>Kalman Filter</a></li><li data-subkey="sec4sub0"><a href="/Threshold-ARMA-TARSTAR-in-R.html" title="TAR and STAR Models"><span class="progress-dot"></span>TAR and STAR Models</a></li><li data-subkey="sec4sub0"><a href="/Forecast-Reconciliation-in-R.html" title="Forecast Reconciliation"><span class="progress-dot"></span>Forecast Reconciliation</a></li><li data-subkey="sec4sub0"><a href="/Hierarchical-Time-Series-in-R.html" title="Hierarchical Time Series"><span class="progress-dot"></span>Hierarchical Time Series</a></li><li data-subkey="sec4sub0"><a href="/MinT-Reconciliation-in-R.html" title="MinT Reconciliation"><span class="progress-dot"></span>MinT Reconciliation</a></li><li data-subkey="sec4sub0"><a href="/Benchmark-Forecasts-in-R.html" title="Benchmark Forecasts"><span class="progress-dot"></span>Benchmark Forecasts</a></li><li data-subkey="sec4sub0"><a href="/Time-Series-Features-in-R.html" title="Time Series Features"><span class="progress-dot"></span>Time Series Features</a></li><li data-subkey="sec4sub0"><a href="/Time-Series-Transformations-in-R.html" title="Box-Cox Transformations"><span class="progress-dot"></span>Box-Cox Transformations</a></li><li data-subkey="sec4sub0"><a href="/Feature-Engineering-for-Forecasting-in-R.html" title="Feature Engineering for Forecasting"><span class="progress-dot"></span>Feature Engineering for Forecasting</a></li><li data-subkey="sec4sub0"><a href="/Time-Series-Regression-in-R.html" title="Time Series Regression"><span class="progress-dot"></span>Time Series Regression</a></li><li data-subkey="sec4sub0"><a href="/tsibble-in-R.html" title="tsibble Objects"><span class="progress-dot"></span>tsibble Objects</a></li><li data-subkey="sec4sub0"><a href="/Conformal-Prediction-in-R.html" title="Conformal Prediction"><span class="progress-dot"></span>Conformal Prediction</a></li><li data-subkey="sec4sub0"><a href="/Global-Forecasting-Models-in-R.html" title="Global Forecasting Models"><span class="progress-dot"></span>Global Forecasting Models</a></li><li data-subkey="sec4sub0"><a href="/XGBoost-Forecasting-in-R.html" title="Gradient Boosting for Forecasting"><span class="progress-dot"></span>Gradient Boosting for Forecasting</a></li><li data-subkey="sec4sub0"><a href="/Backtesting-Forecasts-in-R.html" title="Backtesting Forecasts"><span class="progress-dot"></span>Backtesting Forecasts</a></li><li data-subkey="sec4sub0"><a href="/Distributional-Forecasts-in-R.html" title="Distributional Forecasts"><span class="progress-dot"></span>Distributional Forecasts</a></li><li data-subkey="sec4sub0"><a href="/Forecast-Scoring-Rules-in-R.html" title="Forecast Scoring Rules"><span class="progress-dot"></span>Forecast Scoring Rules</a></li><li data-subkey="sec4sub0"><a href="/Calendar-Effects-in-R.html" title="Calendar Effects"><span class="progress-dot"></span>Calendar Effects</a></li><li data-subkey="sec4sub0"><a href="/CausalImpact-in-R.html" title="CausalImpact"><span class="progress-dot"></span>CausalImpact</a></li><li data-subkey="sec4sub0"><a href="/Missing-Values-in-Time-Series-in-R.html" title="Missing Values in Time Series"><span class="progress-dot"></span>Missing Values in Time Series</a></li><li data-subkey="sec4sub0"><a href="/Bootstrap-Forecasting-in-R.html" title="Bootstrapping and Bagging"><span class="progress-dot"></span>Bootstrapping and Bagging</a></li><li data-subkey="sec4sub0"><a href="/MSTL-in-R.html" title="MSTL: Multiple Seasonalities"><span class="progress-dot"></span>MSTL: Multiple Seasonalities</a></li><li data-subkey="sec4sub0"><a href="/Multiple-Seasonality-Forecasting-in-R.html" title="Multiple Seasonality"><span class="progress-dot"></span>Multiple Seasonality</a></li><li data-subkey="sec4sub0"><a href="/Deep-Learning-Forecasting-in-R.html" title="Deep Learning for Forecasting"><span class="progress-dot"></span>Deep Learning for Forecasting</a></li><li data-subkey="sec4sub0"><a href="/Granger-Causality-in-R.html" title="Granger Causality and IRFs"><span class="progress-dot"></span>Granger Causality and IRFs</a></li><li data-subkey="sec4sub0"><a href="/Structural-Time-Series-in-R.html" title="Structural Time Series"><span class="progress-dot"></span>Structural Time Series</a></li><li data-subkey="sec4sub0"><a href="/Count-Time-Series-in-R.html" title="Count Time Series (INGARCH)"><span class="progress-dot"></span>Count Time Series (INGARCH)</a></li><li data-subkey="sec4sub0"><a href="/Croston-Method-in-R.html" title="Intermittent Demand (Croston)"><span class="progress-dot"></span>Intermittent Demand (Croston)</a></li><li data-subkey="sec4sub0"><a href="/M-Competition-Lessons-in-R.html" title="M-Competition Lessons"><span class="progress-dot"></span>M-Competition Lessons</a></li><li data-subkey="sec4sub0"><a href="/Batch-Forecasting-in-R.html" title="Batch Forecasting"><span class="progress-dot"></span>Batch Forecasting</a></li><li data-subkey="sec4sub0"><a href="/Forecasting-Short-Time-Series-in-R.html" title="Short and Long Series"><span class="progress-dot"></span>Short and Long Series</a></li><li data-subkey="sec4sub0"><a href="/Forecasting-Structural-Breaks-in-R.html" title="Structural Breaks"><span class="progress-dot"></span>Structural Breaks</a></li><li data-subkey="sec4sub0"><a href="/Forecast-Monitoring-in-R.html" title="Forecast Monitoring"><span class="progress-dot"></span>Forecast Monitoring</a></li><li data-subkey="sec4sub0"><a href="/Forecast-Value-Added-in-R.html" title="Forecast Value Added"><span class="progress-dot"></span>Forecast Value Added</a></li><li data-subkey="sec4sub0"><a href="/Retail-Demand-Forecasting-in-R.html" title="Retail Demand Forecasting"><span class="progress-dot"></span>Retail Demand Forecasting</a></li><li data-subkey="sec4sub0"><a href="/Energy-Load-Forecasting-in-R.html" title="Energy Load Forecasting"><span class="progress-dot"></span>Energy Load Forecasting</a></li><li data-subkey="sec4sub0"><a href="/Time-Series-Foundations-Course.html" title="Time Series Foundations (Course)"><span class="progress-dot"></span>Time Series Foundations (Course)</a></li><li data-subkey="sec4sub0"><a href="/Time-Series-Decomposition-Course.html" title="Time Series Decomposition (Course)"><span class="progress-dot"></span>Time Series Decomposition (Course)</a></li><li data-subkey="sec4sub0"><a href="/Forecasting-Toolbox-Course.html" title="Forecasting Toolbox (Course)"><span class="progress-dot"></span>Forecasting Toolbox (Course)</a></li><li data-subkey="sec4sub0"><a href="/Time-Series-Regression-Course.html" title="Time Series Regression (Course)"><span class="progress-dot"></span>Time Series Regression (Course)</a></li><li data-subkey="sec4sub0"><a href="/Exponential-Smoothing-ETS-Course.html" title="Exponential Smoothing ETS (Course)"><span class="progress-dot"></span>Exponential Smoothing ETS (Course)</a></li><li data-subkey="sec4sub0"><a href="/ARIMA-and-Seasonal-ARIMA-Course.html" title="ARIMA and Seasonal ARIMA (Course)"><span class="progress-dot"></span>ARIMA and Seasonal ARIMA (Course)</a></li><li data-subkey="sec4sub0"><a href="/Dynamic-Regression-and-Complex-Seasonality-Course.html" title="Dynamic Regression and Complex Seasonality (Course)"><span class="progress-dot"></span>Dynamic Regression and Complex Seasonality (Course)</a></li><li data-subkey="sec4sub0"><a href="/State-Space-Models-and-the-Kalman-Filter-Course.html" title="State Space Models and the Kalman Filter (Course)"><span class="progress-dot"></span>State Space Models and the Kalman Filter (Course)</a></li><li data-subkey="sec4sub0"><a href="/Spectral-and-Frequency-Domain-Analysis-Course.html" title="Spectral and Frequency Domain Analysis (Course)"><span class="progress-dot"></span>Spectral and Frequency Domain Analysis (Course)</a></li><li data-subkey="sec4sub0"><a href="/Volatility-Modeling-ARCH-and-GARCH-Course.html" title="Volatility Modeling with ARCH and GARCH (Course)"><span class="progress-dot"></span>Volatility Modeling with ARCH and GARCH (Course)</a></li><li data-subkey="sec4sub0"><a href="/Multivariate-Time-Series-Course.html" title="Multivariate Time Series (Course)"><span class="progress-dot"></span>Multivariate Time Series (Course)</a></li><li data-subkey="sec4sub0"><a href="/Hierarchical-and-Grouped-Forecasting-Course.html" title="Hierarchical and Grouped Forecasting (Course)"><span class="progress-dot"></span>Hierarchical and Grouped Forecasting (Course)</a></li><li data-subkey="sec4sub0"><a href="/Machine-Learning-and-Deep-Forecasting-Course.html" title="Machine Learning and Deep Forecasting (Course)"><span class="progress-dot"></span>Machine Learning and Deep Forecasting (Course)</a></li><li data-subkey="sec4sub0"><a href="/Intervention-Causal-Impact-and-Anomaly-Detection-Course.html" title="Intervention, Causal Impact and Anomaly Detection (Course)"><span class="progress-dot"></span>Intervention, Causal Impact and Anomaly Detection (Course)</a></li><li data-subkey="sec4sub0"><a href="/The-Expert-Edge-Forecasting-Like-a-Pro-Course.html" title="The Expert Edge in Forecasting Like a Pro (Course)"><span class="progress-dot"></span>The Expert Edge in Forecasting Like a Pro (Course)</a></li><li data-subkey="sec4sub0"><a href="/Production-Forecasting-Course.html" title="Production Forecasting (Course)"><span class="progress-dot"></span>Production Forecasting (Course)</a></li></ul></li><li class="sidebar-section"><div class="sidebar-section-header"><span class="sidebar-chevron">▸</span><span class="sec-num">6.</span> <span class="sec-title-t">Advanced R</span><span class="section-meta" data-section-meta></span></div><ul class="sidebar-section-items list-unstyled"><li class="sidebar-divider sidebar-subsection-toggle" data-subkey="sec5sub1" data-collapsed="false"><span class="subsec-chevron">▼</span> Functional Programming</li><li data-subkey="sec5sub1"><a href="/Functional-Programming-in-R.html" title="Functional Programming"><span class="progress-dot"></span>Functional Programming</a></li><li data-subkey="sec5sub1" class="is-quiz"><a href="/R-Functional-Programming-Exercises-quiz.html" title="Functional Programming Quiz"><span class="quiz-marker" aria-hidden="true"><svg viewBox="0 0 24 24" fill="currentColor" aria-hidden="true"><path d="M12 2 4 5.1v5.7c0 4.9 3.4 8.4 8 9.9 4.6-1.5 8-5 8-9.9V5.1L12 2z"/></svg></span>Quiz</a></li><li data-subkey="sec5sub1"><a href="/purrr-map-Variants.html" title="purrr map() Variants"><span class="progress-dot"></span>purrr map() Variants</a></li><li data-subkey="sec5sub1"><a href="/R-Anonymous-Functions.html" title="R Anonymous Functions"><span class="progress-dot"></span>R Anonymous Functions</a></li><li data-subkey="sec5sub1"><a href="/R-Function-Factories.html" title="R Function Factories"><span class="progress-dot"></span>R Function Factories</a></li><li data-subkey="sec5sub1"><a href="/R-Function-Operators.html" title="R Function Operators"><span class="progress-dot"></span>R Function Operators</a></li><li data-subkey="sec5sub1"><a href="/Reduce-Filter-Map-in-R.html" title="Reduce, Filter, Map"><span class="progress-dot"></span>Reduce, Filter, Map</a></li><li data-subkey="sec5sub1"><a href="/Memoization-in-R.html" title="Memoization in R"><span class="progress-dot"></span>Memoization in R</a></li><li data-subkey="sec5sub1"><a href="/Writing-Composable-R-Code.html" title="Composable R Code"><span class="progress-dot"></span>Composable R Code</a></li><li class="sidebar-divider sidebar-subsection-toggle" data-subkey="sec5sub2" data-collapsed="false"><span class="subsec-chevron">▼</span> OOP in R</li><li data-subkey="sec5sub2"><a href="/OOP-in-R.html" title="OOP in R: S3/S4/R6"><span class="progress-dot"></span>OOP in R: S3/S4/R6</a></li><li data-subkey="sec5sub2"><a href="/S3-Classes-in-R.html" title="S3 Classes"><span class="progress-dot"></span>S3 Classes</a></li><li data-subkey="sec5sub2"><a href="/S3-Method-Dispatch-in-R.html" title="S3 Method Dispatch"><span class="progress-dot"></span>S3 Method Dispatch</a></li><li data-subkey="sec5sub2"><a href="/S4-Classes-in-R.html" title="S4 Classes"><span class="progress-dot"></span>S4 Classes</a></li><li data-subkey="sec5sub2"><a href="/S4-Methods-in-R.html" title="S4 Methods & Dispatch"><span class="progress-dot"></span>S4 Methods & Dispatch</a></li><li data-subkey="sec5sub2"><a href="/R6-Classes-in-R.html" title="R6 Classes"><span class="progress-dot"></span>R6 Classes</a></li><li data-subkey="sec5sub2"><a href="/R6-Advanced.html" title="R6 Advanced"><span class="progress-dot"></span>R6 Advanced</a></li><li data-subkey="sec5sub2"><a href="/Operator-Overloading-in-R.html" title="Operator Overloading"><span class="progress-dot"></span>Operator Overloading</a></li><li class="sidebar-divider sidebar-subsection-toggle" data-subkey="sec5sub3" data-collapsed="false"><span class="subsec-chevron">▼</span> How R Works</li><li data-subkey="sec5sub3"><a href="/R-Names-and-Values.html" title="R Names & Values"><span class="progress-dot"></span>R Names & Values</a></li><li data-subkey="sec5sub3"><a href="/R-Assignment-Deep-Dive.html" title="R Assignment Deep Dive"><span class="progress-dot"></span>R Assignment Deep Dive</a></li><li data-subkey="sec5sub3"><a href="/R-Memory-lobstr.html" title="R Memory & lobstr"><span class="progress-dot"></span>R Memory & lobstr</a></li><li data-subkey="sec5sub3"><a href="/R-Environments.html" title="R Environments"><span class="progress-dot"></span>R Environments</a></li><li data-subkey="sec5sub3"><a href="/R-Lexical-Scoping.html" title="Lexical Scoping"><span class="progress-dot"></span>Lexical Scoping</a></li><li data-subkey="sec5sub3"><a href="/R-Closures.html" title="R Closures"><span class="progress-dot"></span>R Closures</a></li><li class="sidebar-divider sidebar-subsection-toggle" data-subkey="sec5sub4" data-collapsed="false"><span class="subsec-chevron">▼</span> Debugging & Performance</li><li data-subkey="sec5sub4"><a href="/R-Conditions-System.html" title="Conditions System"><span class="progress-dot"></span>Conditions System</a></li><li data-subkey="sec5sub4"><a href="/R-Debugging.html" title="Debugging R Code"><span class="progress-dot"></span>Debugging R Code</a></li><li data-subkey="sec5sub4"><a href="/R-Common-Errors.html" title="50 Common R Errors"><span class="progress-dot"></span>50 Common R Errors</a></li><li data-subkey="sec5sub4"><a href="/Parallel-Computing-With-R.html" title="Parallel Computing"><span class="progress-dot"></span>Parallel Computing</a></li><li data-subkey="sec5sub4"><a href="/Strategies-To-Improve-And-Speedup-R-Code.html" title="Speedup R Code"><span class="progress-dot"></span>Speedup R Code</a></li><li data-subkey="sec5sub4" class="is-quiz"><a href="/Shiny-Exercises-in-R-quiz.html" title="Shiny Quiz"><span class="quiz-marker" aria-hidden="true"><svg viewBox="0 0 24 24" fill="currentColor" aria-hidden="true"><path d="M12 2 4 5.1v5.7c0 4.9 3.4 8.4 8 9.9 4.6-1.5 8-5 8-9.9V5.1L12 2z"/></svg></span>Quiz</a></li></ul></li><li class="sidebar-section"><div class="sidebar-section-header"><span class="sidebar-chevron">▸</span><span class="sec-num">7.</span> <span class="sec-title-t">Classic Tutorials</span><span class="section-meta" data-section-meta></span></div><ul class="sidebar-section-items list-unstyled"><li data-subkey="sec6sub0"><a href="/R-Tutorial.html" title="R Tutorial (Classic)"><span class="progress-dot"></span>R Tutorial (Classic)</a></li><li data-subkey="sec6sub0"><a href="/ggplot2-Tutorial-With-R.html" title="ggplot2 Short Tutorial"><span class="progress-dot"></span>ggplot2 Short Tutorial</a></li><li data-subkey="sec6sub0"><a href="/Complete-Ggplot2-Tutorial-Part1-With-R-Code.html" title="ggplot2 Tutorial 1 - Intro"><span class="progress-dot"></span>ggplot2 Tutorial 1 - Intro</a></li><li data-subkey="sec6sub0"><a href="/Complete-Ggplot2-Tutorial-Part2-Customizing-Theme-With-R-Code.html" title="ggplot2 Tutorial 2 - Theme"><span class="progress-dot"></span>ggplot2 Tutorial 2 - Theme</a></li><li data-subkey="sec6sub0"><a href="/Top50-Ggplot2-Visualizations-MasterList-R-Code.html" title="ggplot2 Tutorial 3 - Masterlist"><span class="progress-dot"></span>ggplot2 Tutorial 3 - Masterlist</a></li><li data-subkey="sec6sub0"><a href="/Association-Mining-With-R.html" title="Association Mining"><span class="progress-dot"></span>Association Mining</a></li><li data-subkey="sec6sub0"><a href="/Multi-Dimensional-Scaling-With-R.html" title="Multi Dimensional Scaling"><span class="progress-dot"></span>Multi Dimensional Scaling</a></li><li data-subkey="sec6sub0"><a href="/Optimization-With-R.html" title="Optimization"><span class="progress-dot"></span>Optimization</a></li><li data-subkey="sec6sub0"><a href="/Information-Value-With-R.html" title="InformationValue Package"><span class="progress-dot"></span>InformationValue Package</a></li></ul></li><li class="sidebar-section"><div class="sidebar-section-header"><span class="sidebar-chevron">▸</span><span class="sec-num">8.</span> <span class="sec-title-t">Practice Exercises</span><span class="section-meta" data-section-meta></span></div><ul class="sidebar-section-items list-unstyled"><li class="sidebar-divider sidebar-subsection-toggle" data-subkey="sec7sub1" data-collapsed="false"><span class="subsec-chevron">▼</span> Featured Problem Sets</li><li data-subkey="sec7sub1"><a href="/R-Interview-Questions.html" title="R Interview Questions (Top 50)"><span class="progress-dot"></span>R Interview Questions (Top 50)</a></li><li data-subkey="sec7sub1"><a href="/Statistics-Interview-Questions.html" title="Statistics Interview Questions (25)"><span class="progress-dot"></span>Statistics Interview Questions (25)</a></li><li data-subkey="sec7sub1"><a href="/ML-Interview-Questions-in-R.html" title="ML Interview Questions (25)"><span class="progress-dot"></span>ML Interview Questions (25)</a></li><li data-subkey="sec7sub1"><a href="/Top-20-Bayesian-Problems-in-R.html" title="Top 20 Bayesian Problems"><span class="progress-dot"></span>Top 20 Bayesian Problems</a></li><li data-subkey="sec7sub1"><a href="/Probability-Puzzles-for-Interviews.html" title="Probability Puzzles (Top 20)"><span class="progress-dot"></span>Probability Puzzles (Top 20)</a></li><li data-subkey="sec7sub1"><a href="/AB-Testing-Interview-Cases.html" title="A/B Testing Interview Cases (20)"><span class="progress-dot"></span>A/B Testing Interview Cases (20)</a></li><li data-subkey="sec7sub1"><a href="/SQL-to-dplyr-Translations.html" title="SQL to dplyr (30 Translations)"><span class="progress-dot"></span>SQL to dplyr (30 Translations)</a></li><li data-subkey="sec7sub1"><a href="/Top-25-Regression-Problems-in-R.html" title="Top 25 Regression Problems"><span class="progress-dot"></span>Top 25 Regression Problems</a></li><li data-subkey="sec7sub1"><a href="/Top-20-Time-Series-Problems-in-R.html" title="Top 20 Time Series Problems"><span class="progress-dot"></span>Top 20 Time Series Problems</a></li><li data-subkey="sec7sub1"><a href="/Resampling-Problems-in-R.html" title="The Resampling 15"><span class="progress-dot"></span>The Resampling 15</a></li><li data-subkey="sec7sub1"><a href="/Data-Cleaning-Gauntlet.html" title="Data Cleaning Gauntlet (25)"><span class="progress-dot"></span>Data Cleaning Gauntlet (25)</a></li><li data-subkey="sec7sub1"><a href="/Error-Triage-Drills-in-R.html" title="Error Triage Drills (20)"><span class="progress-dot"></span>Error Triage Drills (20)</a></li><li data-subkey="sec7sub1"><a href="/Regex-Drills-in-R.html" title="The Regex 20"><span class="progress-dot"></span>The Regex 20</a></li><li data-subkey="sec7sub1"><a href="/Dates-and-Times-Drills-in-R.html" title="Dates and Times Drills"><span class="progress-dot"></span>Dates and Times Drills</a></li><li data-subkey="sec7sub1"><a href="/Base-R-Speed-Round.html" title="Base R Speed Round"><span class="progress-dot"></span>Base R Speed Round</a></li><li data-subkey="sec7sub1"><a href="/ggplot2-Recreation-Challenge.html" title="ggplot2 Recreation Challenge"><span class="progress-dot"></span>ggplot2 Recreation Challenge</a></li><li data-subkey="sec7sub1"><a href="/Take-Home-Assignment-Simulator.html" title="Take-Home Simulator"><span class="progress-dot"></span>Take-Home Simulator</a></li><li class="sidebar-divider sidebar-subsection-toggle" data-subkey="sec7sub2" data-collapsed="false"><span class="subsec-chevron">▼</span> Mastery Quizzes (Certificate)</li><li data-subkey="sec7sub2" class="is-quiz"><a href="/R-Beginner-Exercises-quiz.html" title="R Fundamentals Quiz"><span class="quiz-marker" aria-hidden="true"><svg viewBox="0 0 24 24" fill="currentColor" aria-hidden="true"><path d="M12 2 4 5.1v5.7c0 4.9 3.4 8.4 8 9.9 4.6-1.5 8-5 8-9.9V5.1L12 2z"/></svg></span>Quiz</a></li><li data-subkey="sec7sub2" class="is-quiz"><a href="/dplyr-Exercises-in-R-quiz.html" title="dplyr Quiz"><span class="quiz-marker" aria-hidden="true"><svg viewBox="0 0 24 24" fill="currentColor" aria-hidden="true"><path d="M12 2 4 5.1v5.7c0 4.9 3.4 8.4 8 9.9 4.6-1.5 8-5 8-9.9V5.1L12 2z"/></svg></span>Quiz</a></li><li data-subkey="sec7sub2" class="is-quiz"><a href="/ggplot2-Exercises-in-R-quiz.html" title="ggplot2 Quiz"><span class="quiz-marker" aria-hidden="true"><svg viewBox="0 0 24 24" fill="currentColor" aria-hidden="true"><path d="M12 2 4 5.1v5.7c0 4.9 3.4 8.4 8 9.9 4.6-1.5 8-5 8-9.9V5.1L12 2z"/></svg></span>Quiz</a></li><li data-subkey="sec7sub2" class="is-quiz"><a href="/Hypothesis-Testing-Exercises-in-R-quiz.html" title="Hypothesis Testing Quiz"><span class="quiz-marker" aria-hidden="true"><svg viewBox="0 0 24 24" fill="currentColor" aria-hidden="true"><path d="M12 2 4 5.1v5.7c0 4.9 3.4 8.4 8 9.9 4.6-1.5 8-5 8-9.9V5.1L12 2z"/></svg></span>Quiz</a></li><li data-subkey="sec7sub2" class="is-quiz"><a href="/Linear-Regression-Exercises-in-R-quiz.html" title="Linear Regression Quiz"><span class="quiz-marker" aria-hidden="true"><svg viewBox="0 0 24 24" fill="currentColor" aria-hidden="true"><path d="M12 2 4 5.1v5.7c0 4.9 3.4 8.4 8 9.9 4.6-1.5 8-5 8-9.9V5.1L12 2z"/></svg></span>Quiz</a></li><li data-subkey="sec7sub2" class="is-quiz"><a href="/Machine-Learning-Exercises-in-R-quiz.html" title="Machine Learning Quiz"><span class="quiz-marker" aria-hidden="true"><svg viewBox="0 0 24 24" fill="currentColor" aria-hidden="true"><path d="M12 2 4 5.1v5.7c0 4.9 3.4 8.4 8 9.9 4.6-1.5 8-5 8-9.9V5.1L12 2z"/></svg></span>Quiz</a></li><li data-subkey="sec7sub2" class="is-quiz"><a href="/tidyr-Exercises-in-R-quiz.html" title="tidyr Quiz"><span class="quiz-marker" aria-hidden="true"><svg viewBox="0 0 24 24" fill="currentColor" aria-hidden="true"><path d="M12 2 4 5.1v5.7c0 4.9 3.4 8.4 8 9.9 4.6-1.5 8-5 8-9.9V5.1L12 2z"/></svg></span>Quiz</a></li><li data-subkey="sec7sub2" class="is-quiz"><a href="/Time-Series-Exercises-in-R-quiz.html" title="Time Series Quiz"><span class="quiz-marker" aria-hidden="true"><svg viewBox="0 0 24 24" fill="currentColor" aria-hidden="true"><path d="M12 2 4 5.1v5.7c0 4.9 3.4 8.4 8 9.9 4.6-1.5 8-5 8-9.9V5.1L12 2z"/></svg></span>Quiz</a></li><li data-subkey="sec7sub2" class="is-quiz"><a href="/Shiny-Exercises-in-R-quiz.html" title="Shiny Quiz"><span class="quiz-marker" aria-hidden="true"><svg viewBox="0 0 24 24" fill="currentColor" aria-hidden="true"><path d="M12 2 4 5.1v5.7c0 4.9 3.4 8.4 8 9.9 4.6-1.5 8-5 8-9.9V5.1L12 2z"/></svg></span>Quiz</a></li><li data-subkey="sec7sub2" class="is-quiz"><a href="/R-Interview-Questions-quiz.html" title="R Interview Readiness Quiz"><span class="quiz-marker" aria-hidden="true"><svg viewBox="0 0 24 24" fill="currentColor" aria-hidden="true"><path d="M12 2 4 5.1v5.7c0 4.9 3.4 8.4 8 9.9 4.6-1.5 8-5 8-9.9V5.1L12 2z"/></svg></span>Quiz</a></li><li data-subkey="sec7sub2" class="is-quiz"><a href="/R-Functional-Programming-Exercises-quiz.html" title="Functional Programming Quiz"><span class="quiz-marker" aria-hidden="true"><svg viewBox="0 0 24 24" fill="currentColor" aria-hidden="true"><path d="M12 2 4 5.1v5.7c0 4.9 3.4 8.4 8 9.9 4.6-1.5 8-5 8-9.9V5.1L12 2z"/></svg></span>Quiz</a></li><li class="sidebar-divider sidebar-subsection-toggle" data-subkey="sec7sub3" data-collapsed="false"><span class="subsec-chevron">▼</span> R Fundamentals</li><li data-subkey="sec7sub3"><a href="/R-Basics-Exercises.html" title="R Basics (15 problems)"><span class="progress-dot"></span>R Basics (15 problems)</a></li><li data-subkey="sec7sub3"><a href="/R-Vectors-Exercises.html" title="R Vectors (12 problems)"><span class="progress-dot"></span>R Vectors (12 problems)</a></li><li data-subkey="sec7sub3"><a 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class="tool-icon"><svg viewBox="0 0 16 16" width="14" height="14" fill="none" stroke="currentColor" stroke-width="1.4" stroke-linecap="round" stroke-linejoin="round" aria-hidden="true"><path d="M1.5 14h13"/><path d="M2 12h2.6V9.6h2.6V7h2.6V4.4h3.2"/><circle cx="9.8" cy="4.4" r="1" fill="currentColor" stroke="none"/></svg></span><span class="tool-label">Percentile Calculator</span></a></li><li><a href="/tools/iqr-calculator.html"><span class="tool-icon"><svg viewBox="0 0 16 16" width="14" height="14" fill="none" stroke="currentColor" stroke-width="1.3" stroke-linecap="round" stroke-linejoin="round" aria-hidden="true"><path d="M2 8H4.5"/><path d="M2 6.2V9.8"/><rect x="4.5" y="5" width="6" height="6" rx="1"/><path d="M7.3 5V11"/><path d="M10.5 8H12"/><path d="M12 6.2V9.8"/><circle cx="14" cy="8" r="1" fill="currentColor" stroke="none"/></svg></span><span class="tool-label">IQR & Outliers</span></a></li><li><a href="/tools/box-plot-calculator.html"><span class="tool-icon"><svg viewBox="0 0 16 16" width="14" height="14" fill="none" stroke="currentColor" stroke-width="1.2" stroke-linecap="round" stroke-linejoin="round" aria-hidden="true"><path d="M4.4 2.5V4.6M4.4 11.4V13.5"/><rect x="2.7" y="4.6" width="3.4" height="6.8" rx="0.7"/><path d="M2.7 8.2H6.1"/><path d="M11.4 4V6M11.4 12V14"/><rect x="9.7" y="6" width="3.4" height="6" rx="0.7"/><path d="M9.7 9.4H13.1"/></svg></span><span class="tool-label">Box Plot</span></a></li><li><a href="/tools/correlation-matrix-calculator.html"><span class="tool-icon"><svg viewBox="0 0 16 16" width="14" height="14" fill="none" stroke="currentColor" stroke-width="1.2" stroke-linecap="round" stroke-linejoin="round" aria-hidden="true"><rect x="2.4" y="2.4" width="11.2" height="11.2" rx="1"/><path d="M2.4 6.1H13.6M2.4 9.9H13.6M6.1 2.4V13.6M9.9 2.4V13.6"/><rect x="2.4" y="2.4" width="3.7" height="3.7" fill="currentColor" stroke="none" opacity="0.55"/><rect x="6.1" y="6.1" width="3.8" height="3.8" fill="currentColor" stroke="none" opacity="0.55"/><rect x="9.9" y="9.9" width="3.7" height="3.7" fill="currentColor" stroke="none" opacity="0.55"/></svg></span><span class="tool-label">Correlation Matrix</span></a></li><li><a href="/tools/chi-square-calculator.html"><span class="tool-icon"><svg viewBox="0 0 16 16" width="14" height="14" fill="none" stroke="currentColor" stroke-width="1.4" stroke-linecap="round" stroke-linejoin="round" aria-hidden="true"><path d="M4 3c4 3.5 4 6.5 8 10"/><path d="M12 3c-4 3.5-4 6.5-8 10"/></svg></span><span class="tool-label">Chi-Square Test</span></a></li><li><a href="/tools/confidence-interval-calculator.html"><span class="tool-icon"><svg viewBox="0 0 16 16" width="14" height="14" fill="none" stroke="currentColor" stroke-width="1.4" stroke-linecap="round" stroke-linejoin="round" aria-hidden="true"><path d="M3.5 4v8M3.5 4H5M3.5 12H5"/><circle cx="8" cy="8" r="1.4" fill="currentColor" stroke="none"/><path d="M12.5 4v8M12.5 4H11M12.5 12H11"/></svg></span><span class="tool-label">Confidence Interval</span></a></li><li><a href="/tools/margin-of-error-calculator.html"><span class="tool-icon"><svg viewBox="0 0 16 16" width="14" height="14" fill="none" stroke="currentColor" stroke-width="1.4" stroke-linecap="round" stroke-linejoin="round" aria-hidden="true"><path d="M2.5 8H13.5"/><path d="M2.5 8l2.2-2M2.5 8l2.2 2M13.5 8l-2.2-2M13.5 8l-2.2 2"/><circle cx="8" cy="8" r="1.5" fill="currentColor" stroke="none"/></svg></span><span class="tool-label">Margin of Error</span></a></li><li><a href="/tools/bootstrap-ci-calculator.html"><span class="tool-icon"><svg viewBox="0 0 16 16" width="14" height="14" fill="none" stroke="currentColor" stroke-width="1.4" stroke-linecap="round" stroke-linejoin="round" aria-hidden="true"><path d="M13 8a5 5 0 1 1-1.4-3.5"/><path d="M13 2.5V5h-2.5"/></svg></span><span class="tool-label">Bootstrap CI</span></a></li><li><a href="/tools/effect-size-converter.html"><span class="tool-icon"><svg viewBox="0 0 16 16" width="14" height="14" fill="none" stroke="currentColor" stroke-width="1.4" stroke-linecap="round" stroke-linejoin="round" aria-hidden="true"><path d="M2.5 5.5h11M11 3l2.5 2.5L11 8"/><path d="M13.5 10.5h-11M5 8l-2.5 2.5L5 13"/></svg></span><span class="tool-label">Effect Size Converter</span></a></li><li><a href="/tools/meta-analysis-quick-tool.html"><span class="tool-icon"><svg viewBox="0 0 16 16" width="14" height="14" fill="none" stroke="currentColor" stroke-width="1.4" stroke-linecap="round" stroke-linejoin="round" aria-hidden="true"><path d="M8 1.5v10.5"/><path d="M3 3.5h5.5"/><rect x="5.4" y="2.9" width="1.2" height="1.2" fill="currentColor" stroke="none"/><path d="M6.5 6.5h6"/><rect x="9.3" y="5.9" width="1.2" height="1.2" fill="currentColor" stroke="none"/><path d="M4 9.5h4.5"/><rect x="6.1" y="8.9" width="1.2" height="1.2" fill="currentColor" stroke="none"/><path d="M5.5 14l2-1.4 2 1.4-2 1.4z" fill="currentColor" stroke="none"/></svg></span><span class="tool-label">Meta-Analysis</span></a></li><li><a href="/tools/power-analysis.html"><span class="tool-icon"><svg viewBox="0 0 16 16" width="14" height="14" fill="none" stroke="currentColor" stroke-width="1.4" stroke-linecap="round" stroke-linejoin="round" aria-hidden="true"><path d="M9 2L4 9h3.5L7 14l5-7H8.5z"/></svg></span><span class="tool-label">Power Analysis</span></a></li><li><a href="/tools/sample-size-calculator.html"><span class="tool-icon"><svg viewBox="0 0 16 16" width="14" height="14" fill="none" stroke="currentColor" stroke-width="1.4" stroke-linecap="round" stroke-linejoin="round" aria-hidden="true"><path d="M8 14.5V9"/><path d="M8 9L3.5 4.5"/><path d="M8 9l4.5-4.5"/><circle cx="3.5" cy="3" r="1.6"/><circle cx="12.5" cy="3" r="1.6"/></svg></span><span class="tool-label">Sample Size</span></a></li><li><a href="/tools/sample-size-t-test-calculator.html"><span class="tool-icon"><svg viewBox="0 0 16 16" width="14" height="14" fill="none" stroke="currentColor" stroke-width="1.4" stroke-linecap="round" stroke-linejoin="round" aria-hidden="true"><path d="M2.5 2.5v11h11"/><path d="M3.5 12C7 12 6.5 4.5 13.5 4"/><path d="M8 13.5v-4"/></svg></span><span class="tool-label">Sample Size (t Tests)</span></a></li><li><a href="/tools/sample-size-proportion-calculator.html"><span class="tool-icon"><svg viewBox="0 0 16 16" width="14" height="14" fill="none" stroke="currentColor" stroke-width="1.4" stroke-linecap="round" stroke-linejoin="round" aria-hidden="true"><path d="M2.5 2.5v11h11"/><path d="M6 13.5V9.5"/><path d="M11 13.5V5"/></svg></span><span class="tool-label">Sample Size (Proportions)</span></a></li><li><a href="/tools/sample-size-anova-calculator.html"><span class="tool-icon"><svg viewBox="0 0 16 16" width="14" height="14" fill="none" stroke="currentColor" stroke-width="1.4" stroke-linecap="round" stroke-linejoin="round" aria-hidden="true"><path d="M2.5 2.5v11h11"/><path d="M5.5 13.5V10"/><path d="M9 13.5V6"/><path d="M12.5 13.5V8"/></svg></span><span class="tool-label">Sample Size (ANOVA)</span></a></li><li><a href="/tools/survival-power-calculator.html"><span class="tool-icon"><svg viewBox="0 0 16 16" width="14" height="14" fill="none" stroke="currentColor" stroke-width="1.4" stroke-linecap="round" stroke-linejoin="round" aria-hidden="true"><path d="M2 3.5h3.5V7H9v3.5h3.5V13H14"/></svg></span><span class="tool-label">Survival Power</span></a></li><li><a href="/tools/type-i-ii-error-visualizer.html"><span class="tool-icon"><svg viewBox="0 0 16 16" width="14" height="14" fill="none" stroke="currentColor" stroke-width="1.4" stroke-linecap="round" stroke-linejoin="round" aria-hidden="true"><path d="M2 12c1.5 0 2-2 3.5-2S7 12 8 12s2-8 3.5-8S13 12 14.5 12"/><line x1="8" y1="2" x2="8" y2="14" stroke-dasharray="2 2"/></svg></span><span class="tool-label">Type I / II Error</span></a></li><li><a href="/tools/z-score-percentile.html"><span class="tool-icon"><svg viewBox="0 0 16 16" width="14" height="14" fill="none" stroke="currentColor" stroke-width="1.4" stroke-linecap="round" stroke-linejoin="round" aria-hidden="true"><path d="M2 13c2 0 3-1 4-3s1.5-6 2-6 .5 6 2 6 2.5 0 4 0"/><path d="M2 13.5h12"/></svg></span><span class="tool-label">Z-Score & Percentile</span></a></li><li><a href="/tools/normal-distribution-calculator.html"><span class="tool-icon"><svg viewBox="0 0 16 16" width="14" height="14" fill="none" stroke="currentColor" stroke-width="1.4" stroke-linecap="round" stroke-linejoin="round" aria-hidden="true"><path d="M1.5 13c2 0 3-1 4-3s1.5-6 2.5-6 1.5 6 2.5 6 2-1 3.5-1"/><path d="M1.5 13.5h13"/><path d="M5.5 13C6.3 11 7 7 8 4C9 7 9.7 11 10.5 13Z" fill="currentColor" stroke="none" opacity="0.4"/></svg></span><span class="tool-label">Normal Distribution</span></a></li><li><a href="/tools/empirical-rule-calculator.html"><span class="tool-icon"><svg viewBox="0 0 16 16" width="14" height="14" fill="none" stroke="currentColor" stroke-width="1.3" stroke-linecap="round" stroke-linejoin="round" aria-hidden="true"><path d="M1.5 12.5h13"/><path d="M2 12.5C5 12.5 5.2 4 8 4C10.8 4 11 12.5 14 12.5"/><path d="M5.6 12.5C6.5 10.8 7.2 7 8 4C8.8 7 9.5 10.8 10.4 12.5Z" fill="currentColor" stroke="none" opacity="0.32"/><path d="M5.6 12.5V10.2M10.4 12.5V10.2" stroke-dasharray="1.5 1.4"/><path d="M3.4 12.5V11M12.6 12.5V11" stroke-dasharray="1.5 1.4"/></svg></span><span class="tool-label">Empirical Rule</span></a></li><li><a href="/tools/equivalence-noninferiority-calculator.html"><span class="tool-icon"><svg viewBox="0 0 16 16" width="14" height="14" fill="none" stroke="currentColor" stroke-width="1.4" stroke-linecap="round" stroke-linejoin="round" aria-hidden="true"><path d="M3 3.5v9M13 3.5v9"/><path d="M5.5 8h5"/><circle cx="8" cy="8" r="1.3" fill="currentColor" stroke="none"/></svg></span><span class="tool-label">Equivalence / NI</span></a></li><li><a href="/tools/outlier-detection-calculator.html"><span class="tool-icon"><svg viewBox="0 0 16 16" width="14" height="14" fill="none" stroke="currentColor" stroke-width="1.4" stroke-linecap="round" stroke-linejoin="round" aria-hidden="true"><circle cx="5" cy="10" r="1" fill="currentColor" stroke="none"/><circle cx="7.5" cy="8.5" r="1" fill="currentColor" stroke="none"/><circle cx="5.5" cy="12.5" r="1" fill="currentColor" stroke="none"/><circle cx="12" cy="4" r="2.4"/></svg></span><span class="tool-label">Outlier Detection</span></a></li><li><a href="/tools/roc-auc-calculator.html"><span class="tool-icon"><svg viewBox="0 0 16 16" width="14" height="14" fill="none" stroke="currentColor" stroke-width="1.4" stroke-linecap="round" stroke-linejoin="round" aria-hidden="true"><path d="M2.5 13.5L13.5 2.5" stroke-dasharray="2 2"/><path d="M2.5 13.5C2.5 7 7 2.5 13.5 2.5"/></svg></span><span class="tool-label">ROC / AUC</span></a></li><li><a href="/tools/cronbachs-alpha-calculator.html"><span class="tool-icon"><svg viewBox="0 0 16 16" width="14" height="14" fill="none" stroke="currentColor" stroke-width="1.4" stroke-linecap="round" stroke-linejoin="round" aria-hidden="true"><path d="M2 4h5M2 8h5M2 12h5"/><path d="M7 4c3.5 0 3.5 4 6 4M7 12c3.5 0 3.5-4 6-4"/><circle cx="13" cy="8" r="1.2" fill="currentColor" stroke="none"/></svg></span><span class="tool-label">Cronbach's Alpha</span></a></li><li><a href="/tools/cohens-kappa-calculator.html"><span class="tool-icon"><svg viewBox="0 0 16 16" width="14" height="14" fill="none" stroke="currentColor" stroke-width="1.4" stroke-linecap="round" stroke-linejoin="round" aria-hidden="true"><rect x="2.5" y="2.5" width="11" height="11" rx="1"/><path d="M6.17 2.5v11M9.83 2.5v11M2.5 6.17h11M2.5 9.83h11"/><circle cx="4.33" cy="4.33" r="1" fill="currentColor" stroke="none"/><circle cx="8" cy="8" r="1" fill="currentColor" stroke="none"/><circle cx="11.67" cy="11.67" r="1" fill="currentColor" stroke="none"/></svg></span><span class="tool-label">Cohen's Kappa</span></a></li><li><a href="/tools/icc-calculator.html"><span class="tool-icon"><svg viewBox="0 0 16 16" width="14" height="14" fill="none" stroke="currentColor" stroke-width="1.4" stroke-linecap="round" stroke-linejoin="round" aria-hidden="true"><path d="M2.5 2.5V13.5H13.5"/><circle cx="5.6" cy="4.7" r="1" fill="currentColor" stroke="none"/><circle cx="7.2" cy="4.7" r="1" fill="currentColor" stroke="none"/><circle cx="6.4" cy="8" r="1" fill="currentColor" stroke="none"/><circle cx="11" cy="8" r="1" fill="currentColor" stroke="none"/><circle cx="10.2" cy="11.3" r="1" fill="currentColor" stroke="none"/><circle cx="11.8" cy="11.3" r="1" fill="currentColor" stroke="none"/></svg></span><span class="tool-label">ICC Calculator</span></a></li><li><a href="/tools/correlation-calculator.html"><span class="tool-icon"><svg viewBox="0 0 16 16" width="14" height="14" fill="none" stroke="currentColor" stroke-width="1.4" stroke-linecap="round" stroke-linejoin="round" aria-hidden="true"><path d="M2.5 2v11.5h11"/><path d="M4 12.5 13 4"/><circle cx="5" cy="10.5" r=".9" fill="currentColor" stroke="none"/><circle cx="7.5" cy="8.5" r=".9" fill="currentColor" stroke="none"/><circle cx="9.5" cy="7" r=".9" fill="currentColor" stroke="none"/><circle cx="11.5" cy="5" r=".9" fill="currentColor" stroke="none"/></svg></span><span class="tool-label">Correlation</span></a></li><li><a href="/tools/linear-regression-calculator.html"><span class="tool-icon"><svg viewBox="0 0 16 16" width="14" height="14" fill="none" stroke="currentColor" stroke-width="1.4" stroke-linecap="round" stroke-linejoin="round" aria-hidden="true"><path d="M2.5 2v11.5h11"/><path d="M3.8 12.2 13.2 4.2"/><circle cx="5.2" cy="11.4" r=".9" fill="currentColor" stroke="none"/><circle cx="7.4" cy="8.6" r=".9" fill="currentColor" stroke="none"/><circle cx="9.4" cy="7.4" r=".9" fill="currentColor" stroke="none"/><circle cx="11.4" cy="4.8" r=".9" fill="currentColor" stroke="none"/></svg></span><span class="tool-label">Linear Regression</span></a></li><li><a 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<nav class="breadcrumb-nav" aria-label="Breadcrumb"><a href="/">Home</a> <span class="breadcrumb-sep">›</span> <span>Visualization</span> <span class="breadcrumb-sep">›</span> <span class="breadcrumb-current">Accessible Data Visualization in R: Color Vision and Contrast</span></nav>
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<h1>Accessible Data Visualization in R: Color Vision and Contrast</h1>
<p class="lead">Accessible data visualization means every reader can decode your chart, including the roughly 1 in 12 men and 1 in 200 women who see color differently. Two levers do most of the work: choosing colors that survive color blindness and grayscale, and keeping enough brightness contrast between your marks and the background. This tutorial builds both from scratch in R and ggplot2, and you can run every example as you read.</p>
<div class="post-byline" style="color:#6b7280;font-size:14px;margin:2px 0 4px 0;line-height:1.5;">By <strong>Selva Prabhakaran</strong> · July 2026</div><div class="post-verified" style="color:#9aa1ad;font-size:12.5px;margin:0 0 18px 0;">Code examples run against R 4.6.0</div>
<h2>Why do readers see the same chart differently?</h2>
<p>A chart that looks perfectly clear to you can be unreadable to the person sitting next to you. The reason is that human color vision varies, and a surprisingly large slice of your audience does not see the red-versus-green distinction you might be relying on. If your chart's meaning lives entirely in color, part of your audience loses that meaning.</p>
<p>We will work in the tidyverse dialect throughout: <code>ggplot2</code> for the charts and a little <code>dplyr</code> for data. Let's start with an ordinary scatter plot and let ggplot2 pick the colors, the way most people write their first plot.</p>
<div class="webr-container" data-block-title="Load libraries and plot fuel economy by drive type">
<div class="webr-code-block">
<div class="webr-header"><div class="webr-header-left"><span class="webr-header-badge">R</span><span class="webr-header-label">Load libraries and plot fuel economy by drive type</span></div><div class="webr-header-right"><button type="button" class="webr-copy-btn" aria-label="Copy code" title="Copy code"><svg width="14" height="14" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" aria-hidden="true"><rect x="9" y="9" width="13" height="13" rx="2" ry="2"/><path d="M5 15H4a2 2 0 0 1-2-2V4a2 2 0 0 1 2-2h9a2 2 0 0 1 2 2v1"/></svg></button><button class="btn btn-sm btn-primary webr-run-btn" onclick="runWebR(this)">▶ Run <span class="webr-run-shortcut">Ctrl+Enter</span></button></div></div>
<div class="webr-editor" data-language="r"><span class="cl"><span class="nf">library</span>(ggplot2)</span>
<span class="cl"><span class="nf">library</span>(dplyr)</span>
<span class="cl"></span>
<span class="cl"><span class="nf">library</span>(scales)</span>
<span class="cl"><span class="c1"># The mpg data splits 234 cars into three drive types; colour will encode them</span></span>
<span class="cl"><span class="nf">table</span>(mpg<span class="o">$</span>drv)</span>
<span class="cl"><span class="c1">#></span></span>
<span class="cl"><span class="c1">#> 4 f r</span></span>
<span class="cl"><span class="c1">#> 103 106 25</span></span>
<span class="cl"></span>
<span class="cl"><span class="c1"># An everyday scatter: fuel economy by drive type, default ggplot2 colours</span></span>
<span class="cl"><span class="nf">ggplot</span>(mpg, <span class="nf">aes</span>(x <span class="o">=</span> displ, y <span class="o">=</span> hwy, colour <span class="o">=</span> drv)) <span class="o">+</span></span>
<span class="cl"> <span class="nf">geom_point</span>(size <span class="o">=</span> <span class="m">2</span>) <span class="o">+</span></span>
<span class="cl"> <span class="nf">labs</span>(x <span class="o">=</span> <span class="s">"Engine size (litres)"</span>, y <span class="o">=</span> <span class="s">"Highway MPG"</span>, colour <span class="o">=</span> <span class="s">"Drive"</span>)</span></div>
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<p>Those are the three groups we color by: 103 four-wheel, 106 front, and 25 rear-drive cars. Run the plot and you get three colored point clouds, one per drive type. It looks fine. But which three colors did ggplot2 actually choose? We can ask directly. <code>scales::hue_pal()</code> is the function that builds ggplot2's default colors, and calling its result with <code>(3)</code> returns three of them, spaced evenly around a color wheel.</p>
<div class="webr-container" data-block-title="Reveal the default colour values">
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<div class="webr-header"><div class="webr-header-left"><span class="webr-header-badge">R</span><span class="webr-header-label">Reveal the default colour values</span></div><div class="webr-header-right"><button type="button" class="webr-copy-btn" aria-label="Copy code" title="Copy code"><svg width="14" height="14" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" aria-hidden="true"><rect x="9" y="9" width="13" height="13" rx="2" ry="2"/><path d="M5 15H4a2 2 0 0 1-2-2V4a2 2 0 0 1 2-2h9a2 2 0 0 1 2 2v1"/></svg></button><button class="btn btn-sm btn-primary webr-run-btn" onclick="runWebR(this)">▶ Run <span class="webr-run-shortcut">Ctrl+Enter</span></button></div></div>
<div class="webr-editor" data-language="r"><span class="cl"><span class="c1"># What three colours did ggplot2 assign to the three groups?</span></span>
<span class="cl">scales<span class="o">::</span><span class="nf">hue_pal</span>()(<span class="m">3</span>)</span>
<span class="cl"><span class="c1">#> [1] "#F8766D" "#00BA38" "#619CFF"</span></span></div>
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<p>The three hex codes are a salmon red (<code>#F8766D</code>), a green (<code>#00BA38</code>), and a blue (<code>#619CFF</code>). That first pair, a red and a green at similar brightness, is exactly the combination that the most common form of color blindness cannot tell apart. The default palette produces exactly that risky pairing.</p>
<p>To understand why, you need a quick model of how color vision works. Your eye has three kinds of color-sensing cells called cones, tuned to long (reddish), medium (greenish), and short (bluish) wavelengths. Color vision deficiency, often shortened to CVD, happens when one cone type is missing or shifted. That produces four broad types, shown below in order of how common they are.</p>
<p><img src="screenshots/Accessible-Data-Visualization-in-R-cvd-types.webp" alt="The four types of color vision deficiency, arranged by how common they are." class="img-responsive img-zoomable" loading="lazy" width="1940" height="710" /></p>
<p><em>Figure 1: The four types of color vision deficiency, by how common they are.</em></p>
<p>The two red-green types, deuteranopia (green-weak) and protanopia (red-weak), are by far the most frequent and together affect about 8% of men of Northern European descent. Tritanopia (blue-yellow) is rare, and complete monochromacy (no color at all) is rarer still. The practical takeaway is blunt: red versus green is the single riskiest color contrast you can build a chart around.</p>
<div class="callout callout-warning"><div class="callout-label">Warning</div><div class="callout-body"><strong>Never let red versus green carry meaning on its own.</strong> This is the pairing that deuteranopia and protanopia, the two most common deficiencies, collapse into the same muddy tone, so any chart that separates groups only by red and green is unreadable for roughly 1 in 12 male viewers.</div></div>
<section class="tryit-block">
<p><strong>Try it:</strong> Print the five colors ggplot2 would use for a five-group chart, then pick out the pair most likely to be confused as red and green.</p>
<div class="webr-container" data-block-title="Your turn: inspect a five-colour default">
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<div class="webr-header"><div class="webr-header-left"><span class="webr-header-badge">R</span><span class="webr-header-label">Your turn: inspect a five-colour default</span></div><div class="webr-header-right"><button type="button" class="webr-copy-btn" aria-label="Copy code" title="Copy code"><svg width="14" height="14" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" aria-hidden="true"><rect x="9" y="9" width="13" height="13" rx="2" ry="2"/><path d="M5 15H4a2 2 0 0 1-2-2V4a2 2 0 0 1 2-2h9a2 2 0 0 1 2 2v1"/></svg></button><button class="btn btn-sm btn-primary webr-run-btn" onclick="runWebR(this)">▶ Run <span class="webr-run-shortcut">Ctrl+Enter</span></button></div></div>
<div class="webr-editor" data-language="r"><span class="cl"><span class="c1"># Print the 5 default ggplot2 colours with scales::hue_pal()</span></span>
<span class="cl"><span class="c1"># your code here</span></span>
<span class="cl"></span>
<span class="cl"><span class="c1">#> Expected: a character vector of 5 hex codes</span></span></div>
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<div class="webr-editor" data-language="r"><span class="cl">scales<span class="o">::</span><span class="nf">hue_pal</span>()(<span class="m">5</span>)</span>
<span class="cl"><span class="c1">#> [1] "#F8766D" "#A3A500" "#00BF7D" "#00B0F6" "#E76BF3"</span></span></div>
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<p><strong>Explanation:</strong> The red <code>#F8766D</code> and the green <code>#00BF7D</code> sit at similar lightness, so a red-green colorblind reader sees them as nearly the same color. The more groups you add with the default scale, the more likely two of them land in a confusable pair.</p>
</details>
</section>
<h2>What makes a color palette colorblind-safe?</h2>
<p>A <a class="auto-link" href="Publication-Quality-Figures-in-R.html" title="Publication-Ready ggplot2 Figures: The Checklist for Journals and Theses">colorblind-safe palette</a> is one whose colors stay distinct even after a cone type drops out. Two design ideas make that happen. The first is spreading colors apart in more than just hue, so they also differ in brightness. The second is perceptual uniformity, meaning equal steps in your data map to equal-looking steps in color across the whole range. Two families give you this for free in ggplot2.</p>
<p>The first is <strong>viridis</strong>, a set of continuous scales that ship with ggplot2. Viridis was engineered to stay readable under all common CVD types and even in grayscale. Use it for continuous quantities with <code>scale_colour_viridis_c()</code> (or <code>scale_fill_viridis_c()</code>).</p>
<p>The second is <strong>Okabe-Ito</strong>, a <a class="auto-link" href="ggplot2-scale_color_brewer-in-R.html" title="ggplot2 scale_color_brewer() in R: ColorBrewer Palettes">qualitative palette</a> of eight colors designed by Masataka Okabe and Kei Ito specifically so that no two are confusable under color blindness. It is the go-to choice for categorical groups. ggplot2 does not carry it as a named scale, so we define it as a plain vector of hex codes.</p>
<div class="webr-container" data-block-title="Define the Okabe-Ito palette">
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<div class="webr-header"><div class="webr-header-left"><span class="webr-header-badge">R</span><span class="webr-header-label">Define the Okabe-Ito palette</span></div><div class="webr-header-right"><button type="button" class="webr-copy-btn" aria-label="Copy code" title="Copy code"><svg width="14" height="14" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" aria-hidden="true"><rect x="9" y="9" width="13" height="13" rx="2" ry="2"/><path d="M5 15H4a2 2 0 0 1-2-2V4a2 2 0 0 1 2-2h9a2 2 0 0 1 2 2v1"/></svg></button><button class="btn btn-sm btn-primary webr-run-btn" onclick="runWebR(this)">▶ Run <span class="webr-run-shortcut">Ctrl+Enter</span></button></div></div>
<div class="webr-editor" data-language="r"><span class="cl"><span class="c1"># The eight Okabe-Ito colours, safe across all CVD types</span></span>
<span class="cl">okabe_ito <span class="o"><-</span> <span class="nf">c</span>(<span class="s">"#E69F00"</span>, <span class="s">"#56B4E9"</span>, <span class="s">"#009E73"</span>, <span class="s">"#F0E442"</span>,</span>
<span class="cl"> <span class="s">"#0072B2"</span>, <span class="s">"#D55E00"</span>, <span class="s">"#CC79A7"</span>, <span class="s">"#000000"</span>)</span>
<span class="cl">okabe_ito</span>
<span class="cl"><span class="c1">#> [1] "#E69F00" "#56B4E9" "#009E73" "#F0E442" "#0072B2" "#D55E00" "#CC79A7"</span></span>
<span class="cl"><span class="c1">#> [8] "#000000"</span></span></div>
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<p>That printed vector is just the eight hex codes: orange, sky blue, bluish green, yellow, blue, vermillion, reddish purple, and black. To use them, hand a named subset to <code>scale_colour_manual()</code>, matching each data value to a color. Here is the same scatter from before, now on a safe palette.</p>
<div class="webr-container" data-block-title="Recolour the scatter with Okabe-Ito">
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<div class="webr-header"><div class="webr-header-left"><span class="webr-header-badge">R</span><span class="webr-header-label">Recolour the scatter with Okabe-Ito</span></div><div class="webr-header-right"><button type="button" class="webr-copy-btn" aria-label="Copy code" title="Copy code"><svg width="14" height="14" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" aria-hidden="true"><rect x="9" y="9" width="13" height="13" rx="2" ry="2"/><path d="M5 15H4a2 2 0 0 1-2-2V4a2 2 0 0 1 2-2h9a2 2 0 0 1 2 2v1"/></svg></button><button class="btn btn-sm btn-primary webr-run-btn" onclick="runWebR(this)">▶ Run <span class="webr-run-shortcut">Ctrl+Enter</span></button></div></div>
<div class="webr-editor" data-language="r"><span class="cl"><span class="nf">ggplot</span>(mpg, <span class="nf">aes</span>(x <span class="o">=</span> displ, y <span class="o">=</span> hwy, colour <span class="o">=</span> drv)) <span class="o">+</span></span>
<span class="cl"> <span class="nf">geom_point</span>(size <span class="o">=</span> <span class="m">2</span>) <span class="o">+</span></span>
<span class="cl"> <span class="nf">scale_colour_manual</span>(</span>
<span class="cl"> values <span class="o">=</span> <span class="nf">c</span>(<span class="s">"4"</span> <span class="o">=</span> <span class="s">"#0072B2"</span>, <span class="s">"f"</span> <span class="o">=</span> <span class="s">"#E69F00"</span>, <span class="s">"r"</span> <span class="o">=</span> <span class="s">"#009E73"</span>),</span>
<span class="cl"> labels <span class="o">=</span> <span class="nf">c</span>(<span class="s">"4"</span> <span class="o">=</span> <span class="s">"4WD"</span>, <span class="s">"f"</span> <span class="o">=</span> <span class="s">"Front"</span>, <span class="s">"r"</span> <span class="o">=</span> <span class="s">"Rear"</span>)</span>
<span class="cl"> ) <span class="o">+</span></span>
<span class="cl"> <span class="nf">labs</span>(x <span class="o">=</span> <span class="s">"Engine size (litres)"</span>, y <span class="o">=</span> <span class="s">"Highway MPG"</span>, colour <span class="o">=</span> <span class="s">"Drive"</span>)</span></div>
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<p>The three groups now use blue, orange, and green from Okabe-Ito. These were chosen so they differ in both hue and brightness, which is what keeps them apart when a cone type is missing. For a continuous variable, reach for viridis instead. Below we color the same points by city mileage, a continuous number.</p>
<div class="webr-container" data-block-title="Colour a continuous variable with viridis">
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<div class="webr-header"><div class="webr-header-left"><span class="webr-header-badge">R</span><span class="webr-header-label">Colour a continuous variable with viridis</span></div><div class="webr-header-right"><button type="button" class="webr-copy-btn" aria-label="Copy code" title="Copy code"><svg width="14" height="14" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" aria-hidden="true"><rect x="9" y="9" width="13" height="13" rx="2" ry="2"/><path d="M5 15H4a2 2 0 0 1-2-2V4a2 2 0 0 1 2-2h9a2 2 0 0 1 2 2v1"/></svg></button><button class="btn btn-sm btn-primary webr-run-btn" onclick="runWebR(this)">▶ Run <span class="webr-run-shortcut">Ctrl+Enter</span></button></div></div>
<div class="webr-editor" data-language="r"><span class="cl"><span class="nf">ggplot</span>(mpg, <span class="nf">aes</span>(x <span class="o">=</span> displ, y <span class="o">=</span> hwy, colour <span class="o">=</span> cty)) <span class="o">+</span></span>
<span class="cl"> <span class="nf">geom_point</span>(size <span class="o">=</span> <span class="m">2</span>) <span class="o">+</span></span>
<span class="cl"> <span class="nf">scale_colour_viridis_c</span>() <span class="o">+</span></span>
<span class="cl"> <span class="nf">labs</span>(x <span class="o">=</span> <span class="s">"Engine size (litres)"</span>, y <span class="o">=</span> <span class="s">"Highway MPG"</span>, colour <span class="o">=</span> <span class="s">"City MPG"</span>)</span></div>
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<p>The points run from dark purple (low city MPG) through green to bright yellow (high). Because viridis brightness increases steadily with the value, a reader can rank the points even if they cannot see the hues at all. That is the property a rainbow scale lacks.</p>
<div class="callout callout-insight"><div class="callout-label">Key Insight</div><div class="callout-body"><strong>Viridis is the safe default for continuous color.</strong> Its brightness rises steadily with the data, so it stays readable under every type of color blindness and even in black and white, which is why it beats rainbow-style scales for any quantity you want people to actually rank.</div></div>
<section class="tryit-block">
<p><strong>Try it:</strong> Color the scatter by <code>class</code> (a 7-level category) using the discrete viridis scale instead of a manual palette.</p>
<div class="webr-container" data-block-title="Your turn: viridis discrete by class">
<div class="webr-code-block">
<div class="webr-header"><div class="webr-header-left"><span class="webr-header-badge">R</span><span class="webr-header-label">Your turn: viridis discrete by class</span></div><div class="webr-header-right"><button type="button" class="webr-copy-btn" aria-label="Copy code" title="Copy code"><svg width="14" height="14" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" aria-hidden="true"><rect x="9" y="9" width="13" height="13" rx="2" ry="2"/><path d="M5 15H4a2 2 0 0 1-2-2V4a2 2 0 0 1 2-2h9a2 2 0 0 1 2 2v1"/></svg></button><button class="btn btn-sm btn-primary webr-run-btn" onclick="runWebR(this)">▶ Run <span class="webr-run-shortcut">Ctrl+Enter</span></button></div></div>
<div class="webr-editor" data-language="r"><span class="cl"><span class="nf">ggplot</span>(mpg, <span class="nf">aes</span>(x <span class="o">=</span> displ, y <span class="o">=</span> hwy, colour <span class="o">=</span> class)) <span class="o">+</span></span>
<span class="cl"> <span class="nf">geom_point</span>(size <span class="o">=</span> <span class="m">2</span>) <span class="o">+</span></span>
<span class="cl"> <span class="c1"># add the discrete viridis scale here</span></span>
<span class="cl"> <span class="nf">labs</span>(colour <span class="o">=</span> <span class="s">"Class"</span>)</span>
<span class="cl"></span>
<span class="cl"><span class="c1">#> Expected: the same scatter with a purple-to-yellow viridis colour set</span></span></div>
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<div class="webr-header"><div class="webr-header-left"><span class="webr-header-badge">R</span><span class="webr-header-label">Viridis discrete solution</span></div><div class="webr-header-right"><button type="button" class="webr-copy-btn" aria-label="Copy code" title="Copy code"><svg width="14" height="14" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" aria-hidden="true"><rect x="9" y="9" width="13" height="13" rx="2" ry="2"/><path d="M5 15H4a2 2 0 0 1-2-2V4a2 2 0 0 1 2-2h9a2 2 0 0 1 2 2v1"/></svg></button><button class="btn btn-sm btn-primary webr-run-btn" onclick="runWebR(this)">▶ Run <span class="webr-run-shortcut">Ctrl+Enter</span></button></div></div>
<div class="webr-editor" data-language="r"><span class="cl"><span class="nf">ggplot</span>(mpg, <span class="nf">aes</span>(x <span class="o">=</span> displ, y <span class="o">=</span> hwy, colour <span class="o">=</span> class)) <span class="o">+</span></span>
<span class="cl"> <span class="nf">geom_point</span>(size <span class="o">=</span> <span class="m">2</span>) <span class="o">+</span></span>
<span class="cl"> <span class="nf">scale_colour_viridis_d</span>() <span class="o">+</span></span>
<span class="cl"> <span class="nf">labs</span>(colour <span class="o">=</span> <span class="s">"Class"</span>)</span></div>
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<p><strong>Explanation:</strong> <code>scale_colour_viridis_d()</code> picks seven evenly spaced viridis colors, one per class. The <code>_d</code> suffix means discrete (one color per category); <code>_c</code> means continuous. Even with seven groups the brightness ordering keeps them legible.</p>
</details>
</section>