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<!DOCTYPE html>
<html lang="de" data-theme="dark">
<head>
<meta charset="UTF-8">
<script>(function(){var t=localStorage.getItem('btl-theme');if(t)document.documentElement.setAttribute('data-theme',t);if(t==='light')document.addEventListener('DOMContentLoaded',function(){['btn-theme','btn-th','btn-th-nav','themeBtn'].forEach(function(id){var b=document.getElementById(id);if(b)b.textContent='🌙 Dark';});});})()</script>
<meta name="viewport" content="width=device-width,initial-scale=1">
<title>Bayes Thinking Lab — Dr. Rainer Düsing · Universität Osnabrück</title>
<meta name="description" content="Interaktive Lerntools für Bayesianische Statistik von Dr. Rainer Düsing, Universität Osnabrück. brms-Tutorial, Bayes interaktiv, Prior Predictive Check, MCMC, kausale Inferenz, HDI, ROPE.">
<meta name="keywords" content="Bayesianische Statistik, brms, Prior Predictive Check, MCMC, DAG, kausale Inferenz, HDI, ROPE, R, interaktives Lernen, Statistik Lehre, Rainer Düsing, Düsing Bayes, Universität Osnabrück Bayes, Bayesianische Statistik R, brms Tutorial, Bayes interaktiv, Institut für Psychologie Osnabrück, Forschungsmethodik, bayesian statistics">
<meta name="author" content="Dr. Rainer Düsing">
<meta property="og:title" content="Bayes Thinking Lab — Dr. Rainer Düsing · Universität Osnabrück">
<meta property="og:description" content="Interaktive Lerntools für Bayesianische Statistik von Dr. Rainer Düsing, Universität Osnabrück. brms-Tutorial, Bayes interaktiv, Prior Predictive Check, MCMC.">
<meta property="og:type" content="website">
<meta property="og:url" content="https://www.bayes-thinking-lab.uni-osnabrueck.de/index_de.html">
<meta property="og:site_name" content="Bayes Thinking Lab">
<link rel="canonical" href="https://www.bayes-thinking-lab.uni-osnabrueck.de/index_de.html">
<link rel="author" href="https://www.researchgate.net/profile/Rainer-Duesing">
<script type="application/ld+json">
{
"@context": "https://schema.org",
"@graph": [
{
"@type": "WebSite",
"name": "Bayes Thinking Lab",
"url": "https://www.bayes-thinking-lab.uni-osnabrueck.de/",
"description": "Interaktive Lerntools für Bayesianische Statistik — brms-Tutorial, Prior Predictive Check, MCMC, kausale Inferenz",
"inLanguage": "de",
"author": { "@id": "#author" }
},
{
"@type": "Person",
"@id": "#author",
"name": "Rainer Düsing",
"givenName": "Rainer",
"familyName": "Düsing",
"honorificPrefix": "Dr.",
"jobTitle": "Forschungsmethodik, Diagnostik und Evaluation",
"affiliation": {
"@type": "EducationalOrganization",
"name": "Universität Osnabrück",
"department": "Institut für Psychologie",
"url": "https://www.uni-osnabrueck.de"
},
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"https://scholar.google.de/citations?user=HXxlPgIAAAAJ&hl=de",
"https://www.linkedin.com/in/rainer-d%C3%BCsing-aaa367348/"
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</script>
<style>
@import url('https://fonts.googleapis.com/css2?family=DM+Mono:ital,wght@0,300;0,400;0,500;1,400&family=Fraunces:ital,opsz,wght@0,9..144,200;0,9..144,300;0,9..144,600;0,9..144,700;1,9..144,200;1,9..144,300;1,9..144,400&display=swap');
/* ─── Design Tokens ───────────────────────────────── */
:root {
--bg: #f0ead8;
--paper: #f8f3e8;
--ink: #18130e;
--ink2: #5a4f42;
--ink3: #8a7f72;
--a1: #c94a2a;
--a2: #2a6e8a;
--a3: #5a8a2a;
--a4: #7a3a8a;
--a5: #b85c00;
--a6: #0e7c7b;
--grid: #ddd5c5;
--panel: #e8e0ce;
--border: #c8bfaa;
--warm: #c8a96e;
--l-min: 22%; --l-max: 62%; --l-amp: 17%;
}
[data-theme="dark"] {
--bg: #0c0f14;
--paper: #111520;
--ink: #ece6d8;
--ink2: #8a8070;
--ink3: #5a5448;
--a1: #e8614a;
--a2: #4ab0d8;
--a3: #80cb52;
--a4: #c87ad8;
--a5: #e07830;
--a6: #2bc7c4;
--grid: #1e242e;
--panel: #171d28;
--border: #2a3040;
--warm: #c8a96e;
--l-min: 34%; --l-max: 82%; --l-amp: 26%;
}
/* ─── Tool-Farbsystem: 1 Farbe pro Sektion, monotone Tonabstufung je Tool ───
Zuordnung: 0 Grundlagen=Teal, I Fundament=Rot-Orange, II Bayes=Lila,
III Small Worlds=Orange, IV Workflow=Oliv, V Entscheidung=Blau.
Jedes Tool bekommt per role-1..6 (t von -1 bis +1) eine Schattierung der
eigenen Sektionsfarbe statt einer beliebigen Fremdfarbe. */
.role-1 { --tl-t: -1; --tl-s: -16%; }
.role-2 { --tl-t: -0.6; --tl-s: -9.6%; }
.role-3 { --tl-t: -0.2; --tl-s: -3.2%; }
.role-4 { --tl-t: 0.2; --tl-s: 3.2%; }
.role-5 { --tl-t: 0.6; --tl-s: 9.6%; }
.role-6 { --tl-t: 1; --tl-s: 16%; }
.role-1, .role-2, .role-3, .role-4, .role-5, .role-6 { --tl-l: calc(var(--tl-t) * var(--l-amp)); }
.role-1, .role-2, .role-3 { --tl-h: calc(var(--tl-t) * var(--spread-neg, 40)); }
.role-4, .role-5, .role-6 { --tl-h: calc(var(--tl-t) * var(--spread-pos, 40)); }
.tool-section { --sec-l: var(--sec-l-light); }
[data-theme="dark"] .tool-section { --sec-l: var(--sec-l-dark); }
.role-1, .role-2, .role-3, .role-4, .role-5, .role-6 {
--tonalB: hsl(
calc(var(--sec-h) + var(--tl-h, 0)),
clamp(15%, calc(var(--sec-s) + var(--tl-s, 0%)), 96%),
clamp(var(--l-min), calc(var(--sec-l) + var(--tl-l, 0%)), var(--l-max))
);
--card-accent: var(--tonalB);
}
.sec-grundlagen { --sec-h: 180; --sec-s: 80%; --sec-l-light: 38%; --sec-l-dark: 48%; --spread-neg: 40; --spread-pos: 5; }
.sec-foundations { --sec-h: 12; --sec-s: 65%; --sec-l-light: 46%; --sec-l-dark: 60%; --spread-neg: 39; --spread-pos: 6; }
.sec-bayesian { --sec-h: 288; --sec-s: 41%; --sec-l-light: 47%; --sec-l-dark: 66%; --spread-neg: 40; --spread-pos: 39; }
.sec-smallworlds { --sec-h: 30; --sec-s: 100%; --sec-l-light: 40%; --sec-l-dark: 53%; --spread-neg: 6; --spread-pos: 27; }
.sec-workflow { --sec-h: 90; --sec-s: 53%; --sec-l-light: 47%; --sec-l-dark: 56%; --spread-neg: 27; --spread-pos: 40; }
.sec-decision { --sec-h: 197; --sec-s: 53%; --sec-l-light: 47%; --sec-l-dark: 57%; --spread-neg: 5; --spread-pos: 40; }
*, *::before, *::after { box-sizing: border-box; margin: 0; padding: 0; }
/* Opera / Chrome font smoothing fix */
html {
font-size: 18px;
-webkit-font-smoothing: antialiased;
-moz-osx-font-smoothing: grayscale;
text-rendering: optimizeLegibility;
scroll-behavior: smooth;
}
body {
font-family: 'Fraunces', Georgia, serif;
background: var(--bg);
color: var(--ink);
min-height: 100vh;
transition: background .25s, color .25s;
overflow-x: hidden;
font-weight: 300;
}
/* ─── NAV ─────────────────────────────────────────── */
nav {
position: sticky; top: 0; z-index: 100;
background: var(--paper);
border-bottom: 1.5px solid var(--border);
padding: .7rem 2rem;
display: flex; align-items: center; justify-content: space-between;
backdrop-filter: blur(8px);
}
.nav-brand {
display: flex; align-items: baseline; gap: .5rem;
}
.nav-brand-name {
font-size: 1.35rem; font-weight: 300; letter-spacing: -.02em;
}
.nav-brand-name em { font-style: italic; color: var(--a2); }
.nav-brand-ver {
font-family: 'DM Mono', monospace; font-size: .72rem;
color: var(--ink3); letter-spacing: .05em;
}
.nav-links {
display: flex; align-items: center; gap: 1.5rem;
font-family: 'DM Mono', monospace; font-size: .75rem; color: var(--ink2);
}
.nav-links a {
color: var(--ink2); text-decoration: none; transition: opacity .15s;
}
.nav-links a:hover { opacity: .7; }
.nav-btns { display: flex; gap: .4rem; }
.nbtn {
font-family: 'DM Mono', monospace; font-size: .75rem;
background: var(--panel); border: 1.5px solid var(--border);
color: var(--ink2); padding: .22rem .6rem; cursor: pointer; transition: all .15s;
}
.nbtn:hover { border-color: var(--a2); color: var(--a2); }
.nbtn.act { background: var(--a2); color: var(--paper); border-color: var(--a2); }
/* ─── HERO ────────────────────────────────────────── */
#hero {
position: relative;
padding: 5rem 2rem 4rem;
max-width: 1100px; margin: 0 auto;
display: grid; grid-template-columns: 1fr 1fr;
gap: 3rem; align-items: center;
}
.hero-left {}
.hero-eyebrow {
font-family: 'DM Mono', monospace; font-size: .72rem; letter-spacing: .12em;
text-transform: uppercase; color: var(--a2); margin-bottom: 1rem;
display: flex; align-items: center; gap: .6rem;
}
.hero-eyebrow::before {
content: ''; display: block; width: 28px; height: 1.5px; background: var(--a2);
}
.hero-title {
font-size: 3.4rem; font-weight: 200; line-height: 1.1;
letter-spacing: -.04em; margin-bottom: 1.2rem;
}
.hero-title em { font-style: italic; color: var(--a4); }
.hero-title strong { font-weight: 600; }
.hero-sub {
font-size: 1.1rem; font-weight: 400; color: var(--ink2);
line-height: 1.75; margin-bottom: 1.8rem; max-width: 44ch;
}
.hero-cta {
display: flex; gap: .8rem; flex-wrap: wrap;
}
.btn-primary {
font-family: 'DM Mono', monospace; font-size: .72rem;
background: var(--a4); color: var(--paper); border: none;
padding: .65rem 1.4rem; cursor: pointer; transition: all .18s;
letter-spacing: .04em; text-decoration: none; display: inline-block;
}
.btn-primary:hover { opacity: .88; transform: translateY(-1px); }
.btn-ghost {
font-family: 'DM Mono', monospace; font-size: .72rem;
background: transparent; color: var(--ink2);
border: 1.5px solid var(--border);
padding: .63rem 1.2rem; cursor: pointer; transition: all .18s;
letter-spacing: .04em; text-decoration: none; display: inline-block;
}
.btn-ghost:hover { border-color: var(--a2); color: var(--a2); }
/* Hero right — abstract diagram */
.hero-diagram {
display: flex; justify-content: center; align-items: center;
}
.hero-svg { width: 340px; height: 320px; opacity: .92; }
/* Audience pills */
.audience-bar {
max-width: 1100px; margin: 0 auto 0;
padding: 0 2rem 3rem;
display: flex; gap: 1rem; flex-wrap: wrap;
}
.aud-pill {
display: flex; align-items: center; gap: .5rem;
font-family: 'DM Mono', monospace; font-size: .6rem;
color: var(--ink2); padding: .3rem .7rem;
border: 1px solid var(--grid); background: var(--panel);
}
.aud-dot { width: 7px; height: 7px; border-radius: 50%; }
/* Divider */
.section-divider {
max-width: 1100px; margin: 0 auto;
padding: 0 2rem .5rem;
display: flex; align-items: center; gap: 1rem;
}
.section-divider::before, .section-divider::after {
content: ''; flex: 1; height: 1px; background: var(--grid);
}
.section-divider span {
font-family: 'DM Mono', monospace; font-size: 1.05rem; font-weight: 600;
letter-spacing: .1em; text-transform: uppercase; color: var(--ink3);
white-space: nowrap;
}
/* ─── TRACK BANNER ────────────────────────────────── */
.track-banner {
max-width: 1100px; margin: 2rem auto .4rem;
padding: 0 2rem;
display: grid; grid-template-columns: 1fr 1fr 1fr;
gap: 1px; background: var(--grid);
border: 1px solid var(--grid);
}
.track {
background: var(--paper);
padding: .8rem 1.1rem;
display: flex; flex-direction: column; gap: .2rem;
}
.track-num { font-family: 'DM Mono', monospace; font-size: .5rem; color: var(--ink3); }
.track-name { font-size: .82rem; font-weight: 300; }
.track-level { font-family: 'DM Mono', monospace; font-size: .55rem; color: var(--ink3); }
/* ─── TOOL SECTIONS ───────────────────────────────── */
.tool-section {
max-width: 1100px; margin: 0 auto 3.5rem;
padding: 0 2rem;
}
.section-header {
display: flex; align-items: flex-end; gap: 1rem;
margin-bottom: 1.2rem; padding-bottom: .7rem;
border-bottom: 1.5px solid var(--grid);
}
.section-badge {
font-family: 'DM Mono', monospace; font-size: .5rem;
padding: .15rem .4rem; letter-spacing: .08em; text-transform: uppercase;
align-self: flex-start; margin-top: .25rem;
}
.badge-zero { background: rgba(14,124,123,.15); color: var(--a6); }
.badge-found { background: rgba(201,74,42,.18); color: var(--a1); }
.badge-bayes { background: rgba(122,58,138,.18); color: var(--a4); }
.badge-workflow { background: rgba(90,138,42,.18); color: var(--a3); }
.section-title {
font-size: 1.5rem; font-weight: 200; line-height: 1.2; letter-spacing: -.02em;
}
.section-title em { font-style: italic; }
.section-desc {
margin-left: auto; max-width: 38ch;
font-family: 'DM Mono', monospace; font-size: .6rem;
color: var(--ink2); line-height: 1.7; text-align: right;
}
/* ─── TOOL CARDS ──────────────────────────────────── */
.tool-grid {
display: grid; gap: 1px; background: var(--grid);
border: 1px solid var(--grid);
}
.tool-grid.cols-2 { grid-template-columns: 1fr 1fr; }
.tool-grid.cols-3 { grid-template-columns: 1fr 1fr 1fr; }
.tool-grid.cols-4 { grid-template-columns: 1fr 1fr 1fr 1fr; }
.tool-grid.cols-wide { grid-template-columns: 1.55fr 1fr; }
.tool-grid.cols-stacked { grid-template-columns: 1fr 1fr; }
.tool-grid.cols-stacked .tool-card.featured { grid-column: 1 / -1; }
.tool-grid.cols-top60 { grid-template-columns: 3fr 2fr; }
/* Vertical workflow arrow */
.workflow-arrow-v {
display:flex;justify-content:center;align-items:center;
background:var(--grid);padding:.22rem;font-family:'DM Mono',monospace;
font-size:.75rem;color:var(--ink3);
}
.workflow-arrow-v.a5 { color:var(--a5); }
/* Posterior PPC card — dashed border to signal external Shiny */
.tool-card.external { border:1.5px dashed var(--border); }
.tool-card.external::before { background:var(--a5); }
/* Workflow-supplement callout — connected to a section's goal but NOT a numbered
pipeline step (no code-import/export to neighboring tools); dashed border reuses
the same "not-quite-in-the-pipeline" idiom as .tool-card.external above.
Deliberately blue (--a2) regardless of the host section's own accent — this is
the Advanced Model Builder's own identity color (its own theme was recolored
to match), not the Workflow section's native green. */
.wf-supplement {
display:flex; align-items:center; gap:.65rem; background:var(--paper);
border:1px dashed var(--a2); border-left:3px dashed var(--a2);
padding:.55rem .9rem; margin-bottom:1.1rem; text-decoration:none;
font-family:'DM Mono',monospace; transition:border-color .15s, background .15s;
}
.wf-supplement:hover { background:var(--panel); }
.wf-supplement .wfs-icon { font-size:1.15rem; color:var(--a2); flex-shrink:0; }
.wf-supplement .wfs-body { font-size:.72rem; color:var(--ink2); line-height:1.6; }
.wf-supplement .wfs-body strong { color:var(--ink); }
.wf-supplement .wfs-cta { margin-left:auto; flex-shrink:0; color:var(--a2); font-size:.75rem; white-space:nowrap; }
/* Thinking Simulator as banner + 3 pillars below */
.tool-grid.cols-banner { grid-template-columns: 1fr 1fr 1fr; }
.tool-grid.cols-banner .tc-banner { grid-column: 1 / -1; }
.tc-banner .tc-desc { column-count: 2; column-gap: 1.8rem; }
/* 4-card intuition layout: Simulator big top-left, Prior Lab top-right, MCMC+Interactive bottom 50:50 */
.tool-grid.cols-intuition { grid-template-columns: 3fr 2fr; grid-template-rows: auto auto; }
.tool-grid.cols-intuition .tc-hero { grid-column:1; grid-row:1; }
.tool-grid.cols-intuition .tc-prior { grid-column:2; grid-row:1; }
.tool-grid.cols-intuition .tc-mcmc { grid-column:1; grid-row:2; }
.tool-grid.cols-intuition .tc-bayes { grid-column:2; grid-row:2; }
.tool-card {
background: var(--paper); padding: 1.5rem 1.8rem;
display: flex; flex-direction: column; gap: .9rem;
transition: background .18s; position: relative; overflow: hidden;
text-decoration: none; color: inherit; cursor: pointer;
}
.tool-card::before {
content: ''; position: absolute; top: 0; left: 0;
width: 3px; height: 0; background: var(--card-accent, var(--a2));
transition: height .22s ease;
}
.tool-card:hover { background: var(--panel); }
.tool-card:hover::before { height: 100%; }
.tc-top { display: flex; align-items: flex-start; justify-content: space-between; gap: 1rem; }
.tc-icon {
width: 42px; height: 42px; border-radius: 0;
display: flex; align-items: center; justify-content: center;
font-size: 1.3rem; flex-shrink: 0;
border: 1.5px solid var(--grid);
background: var(--bg);
}
.tc-tags { display: flex; flex-wrap: wrap; gap: .28rem; justify-content: flex-end; }
.tc-tag {
font-family: 'DM Mono', monospace; font-size: .5rem;
padding: .08rem .28rem; letter-spacing: .05em;
border: 1px solid var(--grid); color: var(--ink3);
}
.tc-name {
font-size: 1.15rem; font-weight: 300; line-height: 1.2;
letter-spacing: -.01em;
}
.tc-name em { font-style: italic; color: var(--card-accent, var(--a2)); }
.tc-desc {
font-family: 'DM Mono', monospace; font-size: .68rem;
color: var(--ink2); line-height: 1.8; flex: 1;
}
.tc-footer {
display: flex; align-items: center; justify-content: space-between;
padding-top: .65rem; border-top: 1px solid var(--grid);
}
.tc-level {
font-family: 'DM Mono', monospace; font-size: .58rem;
color: var(--ink3); letter-spacing: .04em;
}
.tc-launch {
font-family: 'DM Mono', monospace; font-size: .65rem;
color: var(--card-accent, var(--a2)); display: flex; align-items: center; gap: .25rem;
transition: gap .15s;
}
.tool-card:hover .tc-launch { gap: .5rem; }
.tc-launch::after { content: '→'; }
/* Flow connector between sections */
.flow-connector {
max-width: 1100px; margin: 0 auto;
padding: 0 2rem 1rem;
display: flex; align-items: center; gap: .6rem;
}
.flow-dot { width: 8px; height: 8px; border-radius: 50%; flex-shrink: 0; }
.flow-line { flex: 1; height: 1px; background: var(--grid); }
.flow-txt {
font-family: 'DM Mono', monospace; font-size: 1.05rem; font-weight: 600;
color: var(--ink3); white-space: nowrap; letter-spacing: .04em;
}
/* ─── ABOUT / PHILOSOPHY ──────────────────────────── */
#about {
background: var(--paper); border-top: 1.5px solid var(--border);
border-bottom: 1.5px solid var(--border); margin: 2rem 0;
padding: 3.5rem 2rem;
}
.about-inner {
max-width: 1100px; margin: 0 auto;
display: grid; grid-template-columns: 1fr 1.4fr; gap: 4rem; align-items: start;
}
.about-left h2 {
font-size: 2rem; font-weight: 200; letter-spacing: -.03em;
line-height: 1.2; margin-bottom: .8rem;
}
.about-left h2 em { font-style: italic; color: var(--a4); }
.about-left p {
font-size: 1rem; font-weight: 400; color: var(--ink2);
line-height: 1.85; max-width: 36ch;
}
.about-right { display: flex; flex-direction: column; gap: 1.2rem; }
.about-point {
display: flex; gap: 1rem; align-items: flex-start;
padding-bottom: 1.2rem; border-bottom: 1px solid var(--grid);
}
.about-point:last-child { border-bottom: none; padding-bottom: 0; }
.ap-num {
font-family: 'DM Mono', monospace; font-size: .65rem;
color: var(--a4); min-width: 1.5rem; margin-top: .2rem;
}
.ap-title {
font-size: 1rem; font-weight: 300; margin-bottom: .28rem;
}
.ap-title em { font-style: italic; color: var(--a4); }
.ap-desc {
font-family: 'DM Mono', monospace; font-size: .68rem;
color: var(--ink2); line-height: 1.75;
}
/* Featured card — Thinking Simulator hero */
.tool-card.featured {
background: var(--paper);
border-top: 3px solid var(--a4);
position: relative;
}
.tool-card.featured::after {
content: 'EINSTIEG EMPFOHLEN';
position: absolute; top: -.1px; right: 1.4rem;
font-family: 'DM Mono', monospace; font-size: .48rem;
background: var(--a4); color: var(--paper);
padding: .12rem .5rem; letter-spacing: .1em;
}
.tool-card.featured .tc-name { font-size: 1.3rem; }
.tool-card.featured .tc-desc { font-size: .72rem; line-height: 1.85; }
.tc-starter-badges {
display: flex; gap: .4rem; flex-wrap: wrap; margin-top: .1rem;
}
.tc-starter-badge {
font-family: 'DM Mono', monospace; font-size: .56rem;
padding: .15rem .45rem;
background: rgba(122,58,138,.12); color: var(--a4);
border: 1px solid rgba(122,58,138,.25);
}
/* ─── FOOTER ──────────────────────────────────────── */
footer {
padding: 2rem; text-align: center;
font-family: 'DM Mono', monospace; font-size: .58rem;
color: var(--ink3); border-top: 1px solid var(--grid);
display: flex; flex-direction: column; gap: .5rem; align-items: center;
}
footer a { color: var(--a2); text-decoration: none; }
footer a:hover { text-decoration: underline; }
.footer-links { display: flex; gap: 1.5rem; }
/* ─── RESPONSIVE ──────────────────────────────────── */
@media (max-width: 900px) {
#hero { grid-template-columns: 1fr; gap: 2rem; padding: 3rem 1.2rem 2rem; }
.hero-diagram { display: none; }
.hero-title { font-size: 2.4rem; }
.track-banner { grid-template-columns: 1fr; }
.tool-grid.cols-2, .tool-grid.cols-3, .tool-grid.cols-4, .tool-grid.cols-wide { grid-template-columns: 1fr; }
.about-inner { grid-template-columns: 1fr; gap: 2rem; }
nav { padding: .5rem 1.2rem; }
.nav-links { display: none; }
}
/* ─── SIDE TOC ────────────────────────────────────── */
#toc-wrap{
position:fixed;left:0;top:50%;transform:translateY(-50%);
z-index:200;display:flex;align-items:flex-start;
}
#toc-tab{
writing-mode:vertical-rl;text-orientation:mixed;
background:var(--paper);border:1.5px solid var(--border);border-left:none;
padding:.55rem .28rem;font-family:'DM Mono',monospace;font-size:.52rem;
letter-spacing:.1em;text-transform:uppercase;color:var(--ink3);
cursor:pointer;user-select:none;transition:color .15s,background .15s;
border-radius:0 3px 3px 0;
}
#toc-tab:hover{color:var(--a2);background:var(--panel)}
#toc-panel{
background:var(--paper);border:1.5px solid var(--border);border-left:none;
padding:.8rem 1rem;min-width:168px;
display:none;flex-direction:column;gap:.1rem;
box-shadow:3px 3px 0 var(--shadow);
}
#toc-panel.open{display:flex}
.toc-sect{
font-family:'DM Mono',monospace;font-size:.52rem;
letter-spacing:.08em;text-transform:uppercase;
color:var(--ink3);margin-top:.55rem;margin-bottom:.08rem;
}
.toc-sect:first-child{margin-top:0}
.toc-link{
font-family:'DM Mono',monospace;font-size:.65rem;
color:var(--ink2);text-decoration:none;padding:.16rem .3rem;
border-left:2px solid transparent;transition:all .12s;display:block;
}
.toc-link:hover{color:var(--a2);border-left-color:var(--a2);padding-left:.5rem}
/* ─── ANIMATIONS ──────────────────────────────────── */
@keyframes fadeUp {
from { opacity: 0; transform: translateY(18px); }
to { opacity: 1; transform: translateY(0); }
}
.fade-up { opacity: 0; animation: fadeUp .5s ease forwards; }
.fade-up:nth-child(1) { animation-delay: .05s; }
.fade-up:nth-child(2) { animation-delay: .12s; }
.fade-up:nth-child(3) { animation-delay: .19s; }
.fade-up:nth-child(4) { animation-delay: .26s; }
.fade-up:nth-child(5) { animation-delay: .33s; }
@keyframes slideIn { from { opacity:0; transform:translateX(12px); } to { opacity:1; transform:translateX(0); } }
/* ─── INTRO BOX ────────────────────────────────────── */
.intro-box {
max-width: 1100px; margin: 0 auto 2rem;
padding: 0 2rem;
}
.intro-box-inner {
background: var(--paper); border: 1.5px solid var(--border);
padding: 1rem 1.5rem; box-shadow: 2px 2px 0 rgba(0,0,0,.06);
}
.intro-label {
font-family: 'DM Mono', monospace; font-size: .55rem;
letter-spacing: .12em; text-transform: uppercase;
color: var(--ink3); margin-bottom: .75rem;
display: flex; align-items: center; gap: .5rem;
}
.intro-label::before { content:''; width:16px; height:1px; background:var(--ink3); }
.intro-cols { display: grid; grid-template-columns: 1fr 1fr 1fr; gap: 1.2rem; }
.intro-col {
display: flex; gap: .55rem; align-items: flex-start;
font-family: 'DM Mono', monospace; font-size: .67rem;
color: var(--ink2); line-height: 1.7;
}
.intro-num {
font-size: 1.7rem; color: var(--a6); min-width: 1rem;
margin-top: .1rem; font-weight: 600; flex-shrink: 0;
}
@media (max-width: 900px) { .intro-cols { grid-template-columns: 1fr; gap: .6rem; } }
/* ─── SECTION HELP BUTTON ──────────────────────────── */
.section-header { position: relative; }
.help-btn {
font-family: 'DM Mono', monospace; font-size: .6rem;
background: transparent; border: 1.5px solid var(--border);
color: var(--ink3); padding: .22rem .55rem;
cursor: pointer; transition: all .15s; letter-spacing: .05em;
flex-shrink: 0; align-self: flex-end; margin-left: .5rem;
white-space: nowrap;
}
.help-btn:hover { border-color: var(--a2); color: var(--a2); }
/* ─── FLOATING HELP PANEL ──────────────────────────── */
#help-panel {
display: none; position: fixed; right: 1.5rem; top: 50%;
transform: translateY(-50%); width: 310px; z-index: 500;
background: var(--paper); border: 1.5px solid var(--border);
box-shadow: 4px 4px 0 rgba(0,0,0,.14);
animation: slideIn .18s ease-out;
}
#help-panel.open { display: block; }
.hp-head {
display: flex; justify-content: space-between; align-items: center;
padding: .55rem .9rem; border-bottom: 1px solid var(--grid);
}
.hp-label {
font-family: 'DM Mono', monospace; font-size: .58rem;
letter-spacing: .1em; text-transform: uppercase; font-weight: 500;
}
.hp-close {
font-family: 'DM Mono', monospace; font-size: .8rem;
background: transparent; border: none; cursor: pointer;
color: var(--ink3); padding: 0 .15rem; line-height: 1;
}
.hp-close:hover { color: var(--ink); }
.hp-body {
padding: .85rem .9rem; font-family: 'DM Mono', monospace;
font-size: .67rem; line-height: 1.8; color: var(--ink2);
max-height: 72vh; overflow-y: auto;
}
.hp-section {
font-size: .52rem; letter-spacing: .1em; text-transform: uppercase;
color: var(--ink3); margin-top: .9rem; margin-bottom: .3rem;
border-bottom: 1px solid var(--grid); padding-bottom: .2rem;
}
.hp-section:first-child { margin-top: 0; }
.hp-body strong { color: var(--ink); }
.hp-seq { padding-left: .1rem; }
.hp-seq li { list-style: none; padding: .1rem 0; }
.hp-seq li::before { color: var(--a2); margin-right: .4rem; font-weight: 600; font-size: 1.7rem; }
.hp-seq li:nth-child(1)::before { content: '①'; }
.hp-seq li:nth-child(2)::before { content: '②'; }
.hp-seq li:nth-child(3)::before { content: '③'; }
.hp-seq li:nth-child(4)::before { content: '④'; }
.hp-seq li:nth-child(5)::before { content: '⑤'; }
.hp-next {
margin-top: .8rem; padding: .45rem .6rem;
border-left: 3px solid var(--a2); font-size: .65rem;
background: var(--panel); color: var(--ink2);
}
</style>
</head>
<body>
<!-- ═══════════════════════════════════════════
SIDE TOC
════════════════════════════════════════════ -->
<div id="toc-wrap">
<div id="toc-tab" onclick="toggleToc()" title="Inhaltsverzeichnis">≡ Inhalt</div>
<div id="toc-panel">
<span class="toc-sect">Einstieg</span>
<a class="toc-link" href="#zero">0 — Grundlagen</a>
<span class="toc-sect">Modelle</span>
<a class="toc-link" href="#foundations">I — LM → GLMM</a>
<span class="toc-sect">Bayes</span>
<a class="toc-link" href="#bayesian">II — Intuition</a>
<a class="toc-link" href="#smallworlds">III — Small Worlds</a>
<a class="toc-link" href="#workflow">IV — Workflow</a>
<span class="toc-sect">Entscheidung</span>
<a class="toc-link" href="#decision">V — Decision</a>
</div>
</div>
<!-- ═══════════════════════════════════════════
NAV
════════════════════════════════════════════ -->
<nav>
<div class="nav-brand">
<span class="nav-brand-name">Bayes <em>Thinking</em> Lab</span>
<span class="nav-brand-ver">v0.9 beta · Dr. Rainer Düsing, Universität Osnabrück</span>
</div>
<div class="nav-links">
<a href="#zero" style="color:var(--a6)">Grundlagen</a>
<a href="#foundations" style="color:var(--a1)">LM → GLMM</a>
<a href="#bayesian" style="color:var(--a4)">Bayesianisch</a>
<a href="#smallworlds" style="color:var(--a5)">Small Worlds</a>
<a href="#workflow" style="color:var(--a3)">Workflow</a>
<a href="#decision" style="color:var(--a2)">Entscheidung</a>
<a href="#about">Über das Projekt</a>
<a href="https://github.com/raduesing/Bayes_Thinking_Lab" target="_blank">GitHub ↗</a>
</div>
<div class="nav-btns">
<a href="index.html" class="nbtn" title="Switch to English" style="display:inline-flex;align-items:center;gap:.3rem"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 60 30" width="18" height="12"><rect width="60" height="30" fill="#012169"/><path d="M0,0 L60,30 M60,0 L0,30" stroke="#fff" stroke-width="6"/><path d="M0,0 L60,30 M60,0 L0,30" stroke="#C8102E" stroke-width="4"/><path d="M30,0 V30 M0,15 H60" stroke="#fff" stroke-width="10"/><path d="M30,0 V30 M0,15 H60" stroke="#C8102E" stroke-width="6"/></svg> EN</a>
<button class="nbtn" id="btn-th" onclick="toggleTheme()">☀ Light</button>
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</nav>
<!-- ═══════════════════════════════════════════
HERO
════════════════════════════════════════════ -->
<section id="hero">
<div class="hero-left">
<div class="hero-eyebrow">Interaktive Statistik · Open Source</div>
<h1 class="hero-title">
Bayes'sches Denken<br>
<em>lernen,</em><br>
<strong>Modelle bauen.</strong>
</h1>
<p class="hero-sub">
Warum überzeuge ich mich durch neue Daten? Was bedeutet ein Prior?
Wie formuliere ich ein hierarchisches Modell in R? Dieses Lab beantwortet
diese Fragen — interaktiv, visuell und direkt praxistauglich mit brms.
</p>
<div class="hero-cta">
<a href="#bayesian" class="btn-primary">Mit Bayes starten →</a>
<a href="#foundations" class="btn-ghost">Grundlagen entdecken</a>
</div>
</div>
<div class="hero-diagram">
<svg class="hero-svg" viewBox="0 0 340 320" xmlns="http://www.w3.org/2000/svg">
<defs>
<marker id="h-arr" markerWidth="6" markerHeight="6" refX="5" refY="3" orient="auto">
<path d="M0,0 L0,6 L6,3 z" fill="currentColor" opacity=".5"/>
</marker>
</defs>
<!-- Hyperprior row -->
<circle cx="120" cy="40" r="26" fill="none" stroke="var(--a4)" stroke-width="2" opacity=".7"/>
<text x="120" y="36" text-anchor="middle" fill="var(--a4)" font-family="Fraunces,serif" font-size="13" font-weight="600">μ<tspan font-size="9" dy="4">α</tspan></text>
<path d="M80,25 Q110,28 90,28" fill="none" stroke="var(--a4)" opacity=".4" stroke-width="1.2"/>
<!-- mini curve μ_α -->
<path d="M104,52 C106,52 108,47 120,47 C132,47 134,52 136,52" fill="none" stroke="var(--a4)" stroke-width="1.1" opacity=".6"/>
<circle cx="220" cy="40" r="26" fill="none" stroke="var(--a4)" stroke-width="2" opacity=".7"/>
<text x="220" y="36" text-anchor="middle" fill="var(--a4)" font-family="Fraunces,serif" font-size="13" font-weight="600">σ<tspan font-size="9" dy="4">α</tspan></text>
<!-- mini curve σ_α (exp shape) -->
<path d="M204,52 L206,48 C208,45 210,48 212,51 C214,53 216,52 220,52 C228,52 234,51 236,52" fill="none" stroke="var(--a4)" stroke-width="1.1" opacity=".6"/>
<!-- Arrows to alpha_j -->
<line x1="132" y1="62" x2="152" y2="108" stroke="var(--a4)" stroke-width="1.5" opacity=".55" marker-end="url(#h-arr)"/>
<line x1="208" y1="62" x2="188" y2="108" stroke="var(--a4)" stroke-width="1.5" opacity=".55" marker-end="url(#h-arr)"/>
<!-- Plate group -->
<rect x="120" y="108" width="100" height="100" rx="8" fill="none" stroke="var(--a4)" stroke-width="1.2" stroke-dasharray="5,3" opacity=".35"/>
<text x="218" y="204" text-anchor="end" fill="var(--a4)" font-family="'DM Mono',monospace" font-size="9" opacity=".65">j = 1…J</text>
<!-- α_j -->
<circle cx="170" cy="135" r="28" fill="var(--paper)" stroke="var(--a2)" stroke-width="2.5"/>
<text x="170" y="130" text-anchor="middle" fill="var(--a2)" font-family="Fraunces,serif" font-size="14" font-weight="600">α<tspan font-size="9" dy="4">j</tspan></text>
<path d="M152,147 C154,147 156,143 170,143 C184,143 186,147 188,147" fill="none" stroke="var(--a2)" stroke-width="1.1" opacity=".75"/>
<!-- β -->
<circle cx="290" cy="145" r="26" fill="var(--paper)" stroke="var(--a3)" stroke-width="2.2"/>
<text x="290" y="141" text-anchor="middle" fill="var(--a3)" font-family="Fraunces,serif" font-size="14" font-weight="600">β</text>
<path d="M274,154 C276,154 278,151 290,151 C302,151 304,154 306,154" fill="none" stroke="var(--a3)" stroke-width="1.1" opacity=".75"/>
<!-- Obs plate -->
<rect x="70" y="230" width="200" height="80" rx="8" fill="none" stroke="var(--a1)" stroke-width="1.2" stroke-dasharray="5,4" opacity=".35"/>
<text x="268" y="305" text-anchor="end" fill="var(--a1)" font-family="'DM Mono',monospace" font-size="9" opacity=".65">i = 1…N</text>
<!-- Det node -->
<circle cx="170" cy="235" r="7" fill="var(--ink2)" opacity=".55"/>
<text x="170" y="222" text-anchor="middle" fill="var(--ink)" font-family="'DM Mono',monospace" font-size="10" font-weight="500" opacity=".8">μᵢ =</text>
<!-- σ -->
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<text x="50" y="231" text-anchor="middle" fill="var(--a5)" font-family="Fraunces,serif" font-size="15" font-weight="600">σ</text>
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<div class="aud-pill"><span class="aud-dot" style="background:var(--a3)"></span>Bachelor-Studium</div>
<div class="aud-pill"><span class="aud-dot" style="background:var(--a2)"></span>Master-Studium</div>
<div class="aud-pill"><span class="aud-dot" style="background:var(--a4)"></span>Promotion & Forschung</div>
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<div class="aud-pill"><span class="aud-dot" style="background:var(--a1)"></span>Klinische Forschung</div>
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ABOUT STRIP
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<h2>Ein kompletter<br><em>Lernpfad.</em></h2>
<p>
24 interaktive Tools — vom linearen Modell bis zur Posterior-Entscheidung.
Jedes Tool läuft vollständig im Browser, ohne Installation, ohne Datenübertragung.
Direkt kopierbarer R-Code (brms) in jedem Schritt des Workflows.
Integriertes Glossar, um neue Begriffe erklärt zu bekommen.
</p>
<p style="margin-top:.9rem;font-size:.88rem;color:var(--ink3)">
Inspiriert von McElreath <em>Statistical Rethinking</em> und Kruschke <em>Doing Bayesian Data Analysis</em>.
Für Bachelor, Master und Forschende gleichermaßen geeignet.
</p>
</div>
<div class="about-right">
<div class="about-point">
<span class="ap-num" style="color:var(--a6)">0–I</span>
<div>
<div class="ap-title">Statistische <em style="color:var(--a6)">Grundlagen</em> & GLMs</div>
<div class="ap-desc">OLS, Residuen, Maximum Likelihood, Linkfunktionen, bedingte Verteilungen, Mixed Models, Ordinal-Logit, Zero-Inflation. 7 Tools — kein Bayes-Vorwissen nötig. Idealer Einstieg und Referenz für alle Niveaus.</div>
</div>
</div>
<div class="about-point">
<span class="ap-num" style="color:var(--a4)">II</span>
<div>
<div class="ap-title">Bayesianische <em style="color:var(--a4)">Intuition</em></div>
<div class="ap-desc">Was bedeutet ein Prior? Wie entsteht ein Posterior? Wie sampelt MCMC? 5 Tools bauen echte Intuition auf — von der Frage „Warum überhaupt Bayes?" über qualitatives Updating und Prior-Auswahl bis zu analytischen Credible-Intervall-Bändern.</div>
</div>
</div>
<div class="about-point">
<span class="ap-num" style="color:var(--a5)">III</span>
<div>
<div class="ap-title">Small <em style="color:var(--a5)">Worlds</em></div>
<div class="ap-desc">„Small Worlds" nach McElreath (<em>Statistical Rethinking</em>, Kap. 2): Modelle als vereinfachte, konsistente Abbilder der Realität konstruieren. Golem Builder: DAGs zeichnen, kausale Struktur klären (Confounder, Collider, d-Separation), Daten simulieren, brms- und glmmTMB-Code exportieren — inklusive Instrumentalvariablen (mehrere IVs), Front Door Criterion (seriell & parallel) und Effektheterogenität (Moderator W). Data Creator: parametrische Datengenerierung für alle Designs und Likelihoods, mit Random-Effects-Formelvorschau und simulationsbasierter Poweranalyse für R.</div>
</div>
</div>
<div class="about-point">
<span class="ap-num" style="color:var(--a3)">IV</span>
<div>
<div class="ap-title">Bayesianischer Modell-<em style="color:var(--a3)">Workflow</em></div>
<div class="ap-desc">Kruschke-Diagramme, brms-Code-Generierung mit Prior-Slidern, Prior und Posterior Predictive Checks, LOO-basierter Modellvergleich. Der vollständige Zyklus von Modellentwurf und Prior-Spezifikation bis zum validierten Modell.</div>
</div>
</div>
<div class="about-point">
<span class="ap-num" style="color:var(--a2)">V</span>
<div>
<div class="ap-title">Posterior-<em style="color:var(--a2)">Entscheidung</em></div>
<div class="ap-desc">HDI, ETI und ROPE: drei parallele Entscheidungslogiken. Erst Konzepte interaktiv erkunden (Decision Lab), dann eigene Posterior-Draws laden, transformieren (Cohen's d, Odds Ratios) und für Publikationen exportieren (Decision Maker). Für kausale Effekte: G-Computation Builder generiert fertigen R-Code für ATE/ATT/ATU — direkt aus dem Golem Builder befüllbar, mit Export in den Decision Maker.</div>
</div>
</div>
</div>
</div>
</section>
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ORIENTIERUNGS-BOX
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<div class="intro-label">Wie benutze ich dieses Lab?</div>
<div class="intro-cols">
<div class="intro-col">
<span class="intro-num">①</span>
<span>Navigiere über die <strong>farbigen Sektionen im Menü</strong> oben (0–V) oder scrolle durch den Lernpfad von oben nach unten.</span>
</div>
<div class="intro-col">
<span class="intro-num">②</span>
<span>Klicke auf <strong>ℹ Hilfe</strong> in jedem Sektions-Header für Lernziele, Voraussetzungen und die empfohlene Reihenfolge der Tools.</span>
</div>
<div class="intro-col">
<span class="intro-num">③</span>
<span>Folge den <strong>Flow-Pfeilen →</strong> zwischen den Sektionen oder springe direkt zu dem Tool, das du gerade brauchst.</span>
</div>
</div>
</div>
</div>
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GLOSSAR-KACHEL
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<div style="font-size:.93rem;font-weight:400;letter-spacing:.01em;">
Statistisches <em style="color:var(--a6)">Glossar</em>
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line-height:1.65;margin-top:.25rem;">
176 Begriffe aus BTL & MethodsLab — Definition, Formel, Intuition.
Kategoriefilter (Bayes, Kausalität, IRT, Reliabilität …), A-Z-Navigation & Volltextsuche.
</div>
</div>
<div style="display:flex;gap:.4rem;flex-wrap:wrap;flex-shrink:0;align-items:center;">
<span class="tc-tag">176 Begriffe</span>
<span class="tc-tag">12 Kategorien</span>
<span class="tc-tag">Suche & A-Z</span>
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Nachschlagen →
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SECTION 0 — STATISTISCHE GRUNDLAGEN
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<span>0 — Statistische Grundlagen</span>
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<div class="tool-section sec-grundlagen">
<div class="section-header">
<span class="section-badge badge-zero">Grundlagen</span>
<h2 class="section-title">Statistische <em style="color:var(--a6)">Grundlagen</em></h2>
<div class="section-desc">Drei konzeptuelle Einstiegstools — ohne R, ohne Bayes. Was ist eine Regression? Wie funktioniert Maximum Likelihood? Und warum reicht das lineare Modell nicht immer? Idealer Start für alle, die Bayesianisches Denken von Grund auf verstehen wollen.</div>
<button class="help-btn" onclick="showHelp('zero')">ℹ Hilfe</button>
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<span style="border:1px solid var(--a3);color:var(--a3);padding:.12rem .4rem">Lernpfad</span>
<span style="color:var(--a2)"><span style="font-size:1.6rem;font-weight:600">①</span> LM interaktiv</span>
<span>→</span>
<span style="color:var(--a5)"><span style="font-size:1.6rem;font-weight:600">②</span> Maximum Likelihood</span>
<span>→</span>
<span style="color:var(--a3)"><span style="font-size:1.6rem;font-weight:600">③</span> Vom LM zum GLM</span>
<span>→</span>
<span style="color:var(--ink2);opacity:.7">Section I: GLM & GLMM</span>
</div>
<div class="tool-grid cols-3 fade-up">
<a href="LM_interactive.html" target="_blank" class="tool-card role-1">
<div class="tc-top">
<div class="tc-icon">📈</div>
<div class="tc-tags">
<span class="tc-tag">Regression</span>
<span class="tc-tag">Residuen</span>
<span class="tc-tag">OLS</span>
<span class="tc-tag">kein R</span>
</div>
</div>
<div class="tc-name">Lineares Modell <em>interaktiv</em></div>
<div class="tc-desc">
Datenpunkte selbst einzeichnen, eine Gerade manuell einpassen — und auf Knopfdruck die optimale OLS-Gerade sehen. Was sind Residuen? Warum minimiert OLS den RSS? Und was bedeutet es, dass die Streuung um die Gerade normalverteilt ist?<br><br>
Mit bedingten Normalverteilungen entlang der Geraden und Live-Vergleich von eigenem RSS vs. OLS-Minimum.
</div>
<div class="tc-footer">
<span class="tc-level">Einstieg · Bachelor</span>
<span class="tc-launch">Ausprobieren</span>
</div>
</a>
<a href="MLE_tool.html" target="_blank" class="tool-card role-4">
<div class="tc-top">
<div class="tc-icon">⛰</div>
<div class="tc-tags">
<span class="tc-tag">Likelihood</span>
<span class="tc-tag">MLE</span>
<span class="tc-tag">Log-Likelihood</span>
<span class="tc-tag">kein R</span>
</div>
</div>
<div class="tc-name">Maximum <em>Likelihood</em></div>
<div class="tc-desc">
Likelihood ≠ Wahrscheinlichkeit — dieser Unterschied wird hier interaktiv erfahrbar. Eine Verteilung über die Daten „schieben" und beobachten, wann der Dichtewert am Datenpunkt maximal wird — das ist MLE.<br><br>
Drei Stufen: ein Datenpunkt → viele Daten und die Likelihood-Landschaft → drei Familien (Normal, Poisson, Bernoulli) mit AIC/BIC-Vergleich.
</div>
<div class="tc-footer">
<span class="tc-level">Einstieg · Bachelor · Master</span>
<span class="tc-launch">Erkunden</span>
</div>
</a>
<a href="GLM_transition.html" target="_blank" class="tool-card role-6">
<div class="tc-top">
<div class="tc-icon">🌉</div>
<div class="tc-tags">
<span class="tc-tag">GLM</span>
<span class="tc-tag">Linkfunktion</span>
<span class="tc-tag">AIC</span>
<span class="tc-tag">kein R</span>
</div>
</div>
<div class="tc-name">Vom LM zum <em>GLM</em></div>
<div class="tc-desc">
Was passiert, wenn man ein lineares Modell auf binäre, Zähl- oder schiefe Daten anwendet? Drei Szenarien zeigen das Problem — und wie GLMs mit passender Verteilung und Linkfunktion es lösen.<br><br>
Fairer AIC-Vergleich LM vs. GLM, visuelle Linkfunktions-Erklärung, direkter Link zu den GLM-Tools in Section I.
</div>
<div class="tc-footer">
<span class="tc-level">Bachelor · Master</span>
<span class="tc-launch">Verstehen</span>
</div>
</a>
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