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 |

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.md for 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

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

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

Folding Options

⏱️ Countdown Timer for Activities

Package: countdown (R package)

#| 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

🤖 Autopilot Compile-Check-Fix Workflow

After creating each lecture, run this workflow:

CYCLE 1: Compilation Check
COMPILE: quarto render "file.qmd" 2>&1
CHECK: Analyze output for errors/warnings
FIX: Apply fixes based on error type
REPEAT: Until clean compilation

CYCLE 2: Font Size Audit (Code Analysis)
SCAN: grep for font-size < 30px or em < 0.75
SCAN: grep for {.smaller} class usage
FIX: Increase fonts to minimum 30px/0.75em
SPLIT: If slide too dense, split into multiple

CYCLE 3: Visual Check (if user provides screenshots)
ANALYZE: Empty space → increase fonts
ANALYZE: Overflow → split slide or reduce slightly
FIX: Apply adjustments
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

📐 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)

:::