Wackerly to QMD Lecture Converter
Wackerly to QMD Lecture Converter
Convert Wackerly’s “Mathematical Statistics and Applications” (7th Edition) textbook chapters into interactive RevealJS lecture presentations.
🎓 Target Audience
Students: Finance and Economics majors at ADA University
Implication: ALL examples, case studies, and practice problems should have financial or economic context. Abstract mathematical examples from Wackerly should be transformed into relatable finance/econ scenarios.
Quick Start Workflow
When creating lectures from a chapter:
- Extract the chapter content from the uploaded PDF using pymupdf
- Read the chapter text to identify definitions, theorems, examples, and figures
- Split into 2-3 lectures based on logical content breaks
- Transform content into QMD slides following the templates
- Transform examples into finance/economics contexts
- Add interactive elements: OJS visualizations, R case studies, quizzes
- Include financial applications relevant to each topic
- Run autopilot optimization: compile → check fonts → fix → recompile
🎯 Critical Design Requirements
Font Size Requirements (MANDATORY)
- Minimum font size: 30pt equivalent (0.75em) for back-row visibility
- Always prioritize readability over fitting more content
- When in doubt, go LARGER
Revealjs Font Size Reference
| CSS em value | Approximate pt | Use Case | |————–|—————-|———-| | 0.6em | ~24pt | ❌ Too small - NEVER use | | 0.75em | ~30pt | ✅ Minimum acceptable | | 0.85em | ~34pt | ✅ Good for dense slides | | 1.0em | ~40pt | ✅ Preferred for text | | 1.2em | ~48pt | ✅ Great for key points |
Case Study Font Sizes
| Slide Type | Font Size | Notes | |————|———–|——-| | Data loading | 30px | One R chunk per slide with code-fold: true | | Visualization | 30px | Separate slide for plots, code-fold: true | | Analysis | 30px | Two-column layout OK with code-fold: true | | Key Findings | 45px | callout-important, three 33% columns with fragments, NO {.smaller} class | | Summary | 30px | No {.smaller} class needed |
Content Strategy
- Split slides when content is dense rather than shrinking text
- One concept per slide is better than cramped content
- Use
{.smaller}class sparingly, only for interactive slides with controls - Maximum 80 words per slide
- Maximum 5 bullet points per slide
Accessing the Book
Method 1: Uploaded PDF (Preferred)
When the user uploads the Wackerly PDF (Mathematical_Statistics_-_7th_Edition_-_Wackerly.pdf):
- Use the extraction script to get chapter content:
python scripts/extract_wackerly.py /path/to/wackerly.pdf ch6 # Or specific pages: python scripts/extract_wackerly.py /path/to/wackerly.pdf 320 340 - Or extract directly with pymupdf:
import fitz doc = fitz.open('/mnt/user-data/uploads/Mathematical_Statistics_-_7th_Edition_-_Wackerly.pdf') # Extract pages (0-indexed) for page_num in range(start-1, end): text = doc[page_num].get_text() - Check
references/wackerly-chapters.mdfor page numbers and content structure
Chapter Page Numbers (PDF pages)
| Chapter | Title | Pages | |———|——-|——-| | 1 | What Is Statistics? | 25-43 | | 2 | Probability | 44-109 | | 3 | Discrete Random Variables | 110-180 | | 4 | Continuous Variables | 181-246 | | 5 | Multivariate Distributions | 247-319 | | 6 | Functions of Random Variables | 320-369 | | 7 | Sampling Distributions & CLT | 370-413 | | 8 | Estimation | 414-467 | | 9 | Point Estimators & Estimation Methods | 468-511 | | 10 | Hypothesis Testing | 512-586 | | 11 | Linear Models | 587-663 | | 12 | Designing Experiments | 664-684 | | 13 | Analysis of Variance | 685-736 | | 14 | Categorical Data | 737-764 | | 15 | Nonparametric Statistics | 765-819 | | 16 | Bayesian Methods | 820-844 |
Method 2: Web Search (Fallback)
If PDF not available, use web_search: "Wackerly Mathematical Statistics" "Definition X.Y"
YAML Frontmatter Template
---
title: "Mathematical Statistics"
subtitle: "Topic Name Here"
author:
- name: "Samir Orujov, PhD"
affiliations:
- name: "ADA University, School of Business"
- name: "Information Communication Technologies Agency, Statistics Unit"
date: today
format:
revealjs:
theme: default
logo: ../ADA.png
transition: slide
slide-number: c/t
chalkboard: true
controls: true
navigation-mode: linear
width: 1280
height: 720
margin: 0.04
min-scale: 0.2
max-scale: 2.0
footer: "Mathematical Statistics - Topic Name"
incremental: false
highlight-style: tango
code-fold: true
menu: true
progress: true
history: true
mouse-wheel: true
overview: true
zoom: true
quiz:
checkKey: 'c'
resetKey: 'r'
shuffleKey: 's'
allowNumberKeys: true
disableOnCheck: false
disableReset: false
shuffleOptions: true
defaultCorrect: "✅ Correct! Well done."
defaultIncorrect: "❌ Not quite. Try again or check the explanation."
includeScore: true
revealjs-plugins:
- quiz
---
Workflow
0. Extract Chapter Content from PDF
Before creating lectures, extract the relevant chapter content:
import fitz
doc = fitz.open('/mnt/user-data/uploads/Mathematical_Statistics_-_7th_Edition_-_Wackerly.pdf')
# Get chapter pages from references/wackerly-chapters.md
start_page, end_page = 320, 369 # Chapter 6 example
for page_num in range(start_page - 1, end_page):
page = doc[page_num]
text = page.get_text()
print(f"=== PAGE {page_num + 1} ===")
print(text)
Key elements to extract:
- Definition numbers and text (e.g., “DEFINITION 6.1”)
- Theorem statements and proofs
- Example problems with solutions
- Figure descriptions (recreate with R/OJS)
- Exercise problems for practice/quiz questions
1. Analyze Chapter Content
Split each Wackerly chapter into 2-3 logical lectures based on:
- Conceptual boundaries: Group related definitions and theorems
- Complexity: ~45-60 min teaching content per lecture
- Dependencies: Earlier concepts before those that build on them
Example split for Chapter 5 (Multivariate Distributions):
- Lecture 1: Joint distributions, marginal distributions
- Lecture 2: Conditional distributions, independence
- Lecture 3: Expected values, covariance, correlation
2. Generate QMD Files
For each lecture, create a .qmd file following the template in references/qmd-template.md.
3. Transform Content
| Wackerly Element | QMD Transformation |
|---|---|
| Definition X.Y | {.callout-note} with 📝 Definition X.Y header |
| Theorem X.Y | {.callout-important} with Theorem X.Y header |
| Example X.Y | Example slide with . . . progressive reveals |
| Proof | Collapsible proof or separate slide if important |
| Exercise | Practice Problems section or Quiz question |
4. Add Interactive Elements
Each lecture MUST include:
- 1-2 OJS visualizations demonstrating key concepts
- 1 R case study with real financial data (use tidyquant for stock data)
- 3-4 quiz questions testing key concepts
- Practice problems adapted from chapter exercises
- 1 Think-Pair-Share activity with countdown timer
📐 Slide Layout Parameters
Slide Dimensions Reference
- Standard Revealjs: 1280×720 pixels
- Usable content area: ~1200×620 (after margins/headers)
Container Font Sizes
| Layout Type | Optimal Font Size | Margin Top | |————-|——————-|————| | Dense interactive | 0.72em - 0.75em | -5px to -10px | | Standard content | 0.8em - 0.85em | 0px | | Sparse content | 0.9em - 1em | 5px |
Column Width Ratios
| Layout | Left (Controls/Text) | Right (Plot) | |——–|———————|————–| | Single plot | 20-25% | 75-80% | | Dual plots | 20% | 40% / 40% | | Text-heavy | 32-35% | 65-68% |
Plot Dimensions (for 1280×720 slides)
| Plot Type | Small | Medium | Large | Max | |———–|——-|——–|——-|—–| | Single 2D | 400×400 | 500×500 | 600×600 | 720×600 | | Single 3D | 420×380 | 500×450 | 580×520 | 650×580 | | Dual plots | 380×380 | 460×460 | 520×520 | - | | Contour | 600×400 | 720×480 | 820×520 | 900×580 |
Callout Box Font Sizing
| Content Density | Font Size | Use Case | |—————–|———–|———-| | Sparse (4 items) | 42-45px | Practice problems, summaries | | Medium (6-8 items) | 36-38px | Definitions, theorems | | Dense (10+ items) | 32-34px | Detailed examples |
Rule: If bottom 1/3 of slide is empty → increase font by 8-10px
🎮 Smartboard Compatibility
Always add event propagation prevention to interactive elements:
viewof mySlider = {
const input = Inputs.range([0, 10], {value: 5, step: 0.1, label: "Parameter:"});
// Prevent slide navigation on touch/click
input.addEventListener('pointerdown', e => e.stopPropagation());
input.addEventListener('touchstart', e => e.stopPropagation());
input.addEventListener('mousedown', e => e.stopPropagation());
input.addEventListener('click', e => e.stopPropagation());
input.addEventListener('wheel', e => e.stopPropagation());
input.addEventListener('pointermove', e => e.stopPropagation());
input.addEventListener('touchmove', e => e.stopPropagation());
input.addEventListener('mousemove', e => e.stopPropagation());
return input;
}
For Plotly 3D containers:
// After creating the plot
const plotDiv = container.querySelector('.js-plotly-plot');
if (plotDiv) {
['pointerdown', 'touchstart', 'mousedown', 'click', 'wheel',
'pointermove', 'touchmove', 'mousemove'].forEach(eventType => {
plotDiv.addEventListener(eventType, e => e.stopPropagation());
});
}
💻 R Code Visibility for Students
Best practice for teaching slides:
#| echo: true # Show code
#| code-fold: true # Collapsed by default
#| code-summary: "📊 Show Code" # Button label
#| message: false
#| warning: false
Statistics Output: Always Use kable() Tables
NEVER use cat(), print(), or sprintf() to display statistics. Always use kable() from the knitr package to produce formatted tables.
| Wrong | Correct |
|---|---|
cat("Mean:", mean(x)) | kable(summary_df, digits = 3) |
print(round(cor_matrix, 3)) | kable(cor_matrix, digits = 3, caption = "Correlation Matrix") |
sprintf("SD: %.4f", sd(x)) | Build a data.frame() and pass to kable() |
Folding Options
| Option | Behavior | |——–|———-| | code-fold: true | Collapsed by default (click to expand) | | code-fold: show | Expanded by default (click to collapse) | | code-fold: false | Always visible, no toggle |
⏱️ Countdown Timer for Activities
Package: countdown (R package)
Basic Usage (Think-Pair-Share, Group Work)
#| echo: false
library(countdown)
countdown(minutes = 4, seconds = 0,
top = 0, right = 0, # Position: top-right corner
font_size = "1.5em",
color_running_background = "#31b09e", # Green while running
color_running_text = "white",
color_finished_background = "#cc3311", # Red when done
color_finished_text = "white",
color_warning_background = "#f7dc6f", # Yellow warning
warn_when = 60, # Warn at 60 seconds left
play_sound = TRUE) # 🔊 Alarm when finished
Activity Duration Guidelines
| Activity Type | Duration | Timer Setting | |—————|———-|—————| | Quick Think | 1 min | minutes = 1 | | Think-Pair-Share | 4 min | minutes = 4 | | Group Problem | 5-8 min | minutes = 5 or minutes = 8 | | Case Study | 10-15 min | minutes = 10 or minutes = 15 |
🤖 Autopilot Compile-Check-Fix Workflow
After creating each lecture, run this workflow:
CYCLE 1: Compilation Check
1. COMPILE: quarto render "file.qmd" 2>&1
2. CHECK: Analyze output for errors/warnings
3. FIX: Apply fixes based on error type
4. REPEAT: Until clean compilation
CYCLE 2: Font Size Audit (Code Analysis)
1. SCAN: grep for font-size < 30px or em < 0.75
2. SCAN: grep for {.smaller} class usage
3. FIX: Increase fonts to minimum 30px/0.75em
4. SPLIT: If slide too dense, split into multiple
CYCLE 3: Visual Check (if user provides screenshots)
1. ANALYZE: Empty space → increase fonts
2. ANALYZE: Overflow → split slide or reduce slightly
3. FIX: Apply adjustments
4. RECOMPILE: Verify changes
Grep Patterns for Font Audit
# Find fonts below 30px
grep -E "font-size:\s*(2[0-9]|1[0-9])px" file.qmd
# Find fonts below 0.75em
grep -E "font-size:\s*0\.[56]" file.qmd
# Find .smaller class usage
grep "{.smaller}" file.qmd
Common Quarto Errors & Fixes
| Error | Fix | |——-|—–| | no package called 'X' | install.packages('X') | | object not found | Check variable scope in R chunks | | unexpected token | Check OJS syntax, missing brackets | | duplicate attribute | Merge width into style attribute | | weight= typo | Change to width= | | Overfull content | Split slide or reduce font by 2-4px | | Empty space | Increase font by 4-10px |
📐 Quick Reference Templates
Two-Column: Controls + Single Large Plot
## 🎮 Interactive: [Title] {.smaller}
:::::: {style="font-size: 0.72em; margin-top: -8px;"}
::::: columns
::: {.column width="25%"}
```{ojs}
// Slider controls + text panel
:::
::: {.column width=”75%”}
// Large plot (width: 820, height: 520)
::: ::::: ::::::
### Three-Column: Controls + 2D + 3D Plots
```markdown
## 🎮 Interactive: [Title] {.smaller}
:::::: {style="font-size: 0.75em; margin-top: -5px;"}
::::: columns
::: {.column width="20%"}
```{ojs}
// Controls + text
:::
::: {.column width=”40%”}
// 2D plot (width: 460, height: 460)
:::
::: {.column width=”40%”}
// 3D plot (width: 480, height: 460)
::: ::::: ::::::
### Think-Pair-Share Activity
```markdown
## 🤝 Think-Pair-Share: [Topic] {.larger}
::::: {style="font-size: 38px;"}
:::: callout-note
## 💭 Activity (4 minutes)
**Problem setup here**
::: columns
::: {.column width="33%"}
**🧠 Think (1 min):**
- Task 1
- Task 2
:::
::: {.column width="33%"}
**👫 Pair (2 min):**
- Discussion point 1
- Discussion point 2
:::
::: {.column width="33%"}
**🗣️ Share (1 min):**
- Synthesis question
:::
:::
::::
:::::
```{r}
#| echo: false
library(countdown)
countdown(minutes = 4, seconds = 0,
top = 0, right = 0,
font_size = "1.5em",
color_running_background = "#31b09e",
color_running_text = "white",
color_finished_background = "#cc3311",
color_finished_text = "white",
warn_when = 60,
play_sound = TRUE)
---
## File Naming
{topic}_lecture{N}.qmd
Examples:
- `multivariate_lecture1.qmd`
- `hypothesis_testing_lecture2.qmd`
- `regression_lecture1.qmd`
## Required Sections (in order)
1. **YAML frontmatter** (see template above)
2. **Learning Objectives** (5 bullet points with action verbs)
3. **Overview** (topics covered today)
4. **Motivation** (why this topic matters)
5. **Content slides** (definitions, theorems, examples)
6. **Interactive visualization** (OJS with smartboard compatibility)
7. **Think-Pair-Share activity** (with countdown timer)
8. **Case Study** (R with financial data, code-fold: true)
9. **Quizzes** (3-4 questions)
10. **Summary** (key takeaways)
11. **Practice Problems** (4-5 problems)
12. **Thank You** (contact info, next class)
13. **Questions** (discussion prompts)
## Slide Design Guidelines
- Use `{.smaller}` class ONLY for interactive slides with controls
- Use `. . .` for progressive reveal in solutions
- Use `{.columns}` with `{.column width="50%"}` for side-by-side content
- Use `{.fragment}` for animated reveals within columns
- Keep math in display mode (`$$...$$`) for important equations
- Use inline math (`$...$`) for references within text
- **Always use `width=` not `weight=`** in column definitions
## 💰 Financial & Economic Applications (CRITICAL)
**ALL examples must have finance/economics context.** Students are finance/econ majors and learn better with relevant applications.
### Concept Transformation Table
| Mathematical Concept | Finance/Economics Application |
|---------------------|-------------------------------|
| Random variables | Asset returns, GDP growth, inflation rates |
| Discrete distributions | Number of defaults, trading days, customer arrivals |
| Continuous distributions | Stock prices, interest rates, exchange rates |
| Joint distributions | Portfolio returns (multiple stocks) |
| Independence | Diversification benefits, uncorrelated assets |
| Conditional probability | Default given recession, returns given market state |
| Covariance/Correlation | Portfolio risk analysis, asset co-movement |
| Expected value | Expected portfolio return, fair price |
| Variance | Volatility, risk measurement |
| Moment generating functions | Option pricing, risk-neutral valuation |
| Order statistics | Best/worst performing assets, VaR |
| Sampling distributions | Estimating market parameters |
| Hypothesis testing | Testing market efficiency, comparing strategies |
| Regression | CAPM, factor models, forecasting |
### Example Transformations
| Wackerly Example | Finance Version |
|------------------|----------------|
| "Balls in urns" | "Stocks in a portfolio" |
| "Defective items" | "Defaulting loans" |
| "Waiting time" | "Time between trades" |
| "Heights of people" | "Daily returns of S&P 500" |
| "Machine failure" | "Market crash probability" |
| "Dice experiment" | "Economic scenarios (boom/recession/stable)" |
### Real Data Sources
- **Stock tickers:** AAPL, MSFT, GOOGL, AMZN, SPY, QQQ, TLT, GLD
- **R packages:** `quantmod`, `tidyquant`, `fredr` (FRED economic data)
- **Economic indicators:** GDP, CPI, unemployment rate, Fed funds rate
### Case Study Ideas by Topic
| Chapter | Case Study |
|---------|------------|
| Probability | Portfolio allocation under uncertainty |
| Discrete RV | Loan default modeling |
| Continuous RV | Stock return distributions |
| Multivariate | Two-asset portfolio optimization |
| Sampling | Estimating market beta |
| Estimation | Confidence intervals for expected returns |
| Hypothesis Testing | Testing CAPM, market efficiency |
| Regression | Factor models, risk decomposition |
## ✅ Quality Checklist
Before finalizing each lecture:
- [ ] YAML frontmatter complete with quiz plugin and scaling settings
- [ ] 5 clear learning objectives with action verbs
- [ ] All Wackerly definitions/theorems properly numbered
- [ ] **All fonts ≥ 30pt (0.75em)** - CRITICAL
- [ ] **All examples have finance/economics context** - CRITICAL
- [ ] Examples have progressive reveal (`. . .`)
- [ ] At least 1 interactive OJS visualization with smartboard compatibility
- [ ] R case study with real financial data and `code-fold: true`
- [ ] Think-Pair-Share activity with countdown timer
- [ ] 3-4 quiz questions with finance/econ scenarios
- [ ] Summary matches learning objectives
- [ ] Next class preview in Thank You slide
- [ ] **Autopilot workflow completed** (compile → check → fix)
- [ ] No slides with > 80 words or > 5 bullet points (split if needed)
- [ ] No abstract "balls in urns" type examples (transform to finance)
## Reference Files
- `references/qmd-template.md` - Complete YAML and slide templates
- `references/slide-patterns.md` - Patterns for different slide types (OJS, R, quizzes)
- `references/wackerly-chapters.md` - Chapter structure, definitions, theorems, page numbers
- `scripts/extract_wackerly.py` - Python script to extract PDF content
---
## 🎮 Interactive Visualization Best Practices
### OJS Plot Errors & Fixes
#### Error: "missing channel value: x1"
**Problem:** Using conditional marks with `&&` operator returns `false` when condition not met, and `false` is not a valid mark.
**Wrong:**
```javascript
marks: [
Plot.contour(data, {...}),
region === "Triangular" && Plot.line(boundary, {...}), // ❌ Returns false
Plot.frame()
]
Correct:
marks: [
Plot.contour(data, {...}),
region === "Triangular" ? Plot.line(boundary, {...}) : null, // ✅ Returns null
Plot.frame()
].filter(Boolean) // Remove null values
Contour Plot Bleeding Across Boundaries
Problem: When support is triangular (e.g., y₂ ≤ y₁), contour interpolation can bleed into forbidden region.
Solution: Add explicit zero-density points in the forbidden region:
jointData = {
const data = [];
for (let i = 0; i < n; i++) {
for (let j = 0; j < n; j++) {
const y1 = i / (n - 1);
const y2 = j / (n - 1);
const inRegion = (region === "Triangular") ? (y2 <= y1) : true;
if (inRegion) {
data.push({y1, y2, density: computeDensity(y1, y2)});
}
}
}
// Add zero-density boundary points for triangular case
if (region === "Triangular") {
for (let i = 0; i < n; i++) {
const y1 = i / (n - 1);
for (let j = Math.ceil(y1 * (n-1)) + 1; j < n; j++) {
const y2 = j / (n - 1);
data.push({y1, y2, density: 0}); // Prevent bleeding
}
}
}
return data;
}
Conditional Slice Visualization
Best practice: Show vertical band + dots instead of dashed line alone
Wrong (hard to see):
marks: [
Plot.ruleX([sliceY1], {stroke: "blue", strokeDasharray: "3,3"}) // ❌ Too subtle
]
Correct (clear visual):
// Create vertical band data
sliceBand = {
const bandwidth = 0.015;
const ymax = region === "Triangular" ? sliceY1 : 1;
return [{x1: sliceY1 - bandwidth, x2: sliceY1 + bandwidth, y1: 0, y2: ymax}];
};
// Create conditional range dots
conditionalDots = {
const points = [];
const ymax = region === "Triangular" ? sliceY1 : 1;
for (let i = 0; i <= 35; i++) {
points.push({y1: sliceY1, y2: (i / 35) * ymax});
}
return points;
};
marks: [
// Semi-transparent band
Plot.rect(sliceBand, {x1: "x1", x2: "x2", y1: "y1", y2: "y2",
fill: "#3b82f6", fillOpacity: 0.12}),
// Dots showing feasible range
Plot.dot(conditionalDots, {x: "y1", y: "y2", r: 3, fill: "#1d4ed8", opacity: 0.9}),
// Solid vertical line
Plot.ruleX([sliceY1], {stroke: "#1d4ed8", strokeWidth: 3})
]
Support Region Notation
Always explicitly state support constraints in both text and plot title:
// In control panel
lesson_html = region === "Rectangular"
? html`<div style="..."><strong>Support:</strong> 0 < Y₁ < 1, 0 < Y₂ < 1<br>Y₂'s range never changes with Y₁.</div>`
: html`<div style="..."><strong>Support:</strong> 0 < Y₂ ≤ Y₁ < 1<br>Knowing Y₁ restricts Y₂ (lower triangle!).</div>`;
// In plot title
title: region === "Rectangular"
? "Rectangle: Support is 0<Y₁<1, 0<Y₂<1 (full square)"
: "Triangle: Support is 0<Y₂≤Y₁<1 (LOWER triangle)"
Educational Context for Interactive Slides
Problem: Plots that just “change” without explanation teach nothing.
Solution: Frame with clear question + educational insight
## 🎮 Interactive: Why Support Shape Determines Independence {.smaller}
**Key insight:** Independence needs both (1) density factors AND (2) rectangular support.
[Controls here]
**Verdict:** [INDEPENDENT or DEPENDENT]
**The Lesson:**
- Rectangle: Knowing Y₁ tells you *nothing* about Y₂'s range
- Triangle: Knowing Y₁ *restricts* Y₂ → information flows between variables
Caption below plot:
html`<div>
${plot}
<div style="margin-top: 5px; font-size: 0.9em;">
<strong>Blue band at Y₁=${sliceY1.toFixed(2)}:</strong> Shows Y₂'s feasible range.
${region === "Triangular"
? `Only [0, ${sliceY1.toFixed(2)}] allowed.`
: "Always [0, 1] allowed."}
</div>
</div>`
OJS Superscripts in Formulas
Problem: ${power} interpolation inside LaTeX breaks compilation
Wrong:
formula = `f(y₁, y₂) = c · y₁^{${power_a}} · y₂^{${power_b}}` // ❌ LaTeX error
Correct - Use HTML:
formula_html = html`<span style="font-size: 1.05em;">
f(y₁, y₂) = c · y₁<sup>${power_a}</sup> · y₂<sup>${power_b}</sup>
</span>`;
md`**Formula:** ${formula_html}`
🎯 Countdown Timer Positioning
Default: Top-right corner
countdown(minutes = 4, top = 0, right = 0, ...)
Bottom-right (better for slides with top content):
countdown(minutes = 4, bottom = 0, right = 0, ...)
⚠️ Common Fragmentation Issues
Problem: . . . Not Working Inside Style Blocks
Wrong:
::: {style="font-size: 36px;"}
. . .
Some content
. . .
More content
:::
Correct - Use {.fragment} divs:
::: {style="font-size: 36px;"}
::: {.fragment}
Some content
:::
::: {.fragment}
More content
:::
:::
Last updated: February 3, 2026 Based on: Dr. Samir Orujov’s lecture format for ADA University Lessons from: multivariate_lecture2.qmd debugging session