Interactive Learning Modules
Hands-On Learning Tools
These browser-based interactive modules provide immediate feedback and engaging visualizations. Each module is designed for discovery learning—students explore concepts through experimentation.
📚 Complete Module Library
🎯 Module Series
1. Checking Normality Series (5 Modules)
Progressive learning sequence for assessing normality assumptions.
Recommended Use
Assign before covering normality in class, or as review before first analysis assignment.
Modules:
Module 1: Introduction to Normality
Foundation concepts and importance
Module 2: Visual Detection
Graphical assessment techniques (histograms, Q-Q plots)
Module 3: Statistical Tests
Formal hypothesis testing (Shapiro-Wilk, etc.)
Module 4: Data Transformations
Techniques to achieve normality (log, sqrt)
Module 5: Nonparametric Alternatives
What to do when normality fails
👨🏫 Instructor Guide
Teaching notes and learning objectives
2. Regression Analysis Series (4 Modules)
Interactive exploration of linear regression with real-world datasets.
Recommended Use
Assign Module 1 before regression lecture, Modules 2-4 as the unit progresses.
Modules:
Module 1: Simple Linear Regression
Core concepts, interpretation, and line of best fit
Module 2: Model Evaluation
R², residuals, and diagnostic plots
Module 3: Multiple Regression
Working with multiple predictors
Module 4: Advanced Topics
Interactions and transformations
👨🏫 Instructor Guide
Teaching notes and assessment rubrics
3. Chi-Square Analysis
Master categorical data analysis through interactive chi-square tests.
Recommended Use
Assign when introducing chi-square or as practice before chi-square assessment.
Chi-Square Interactive Module
Formulate hypotheses, calculate expected frequencies, interpret test statistics
4. Coffee Simulation (Sampling Distributions)
Explore sampling distributions and confidence intervals through a relatable coffee scenario.
Recommended Use
Perfect introduction to inferential statistics—assign BEFORE covering hypothesis testing.
Coffee Shop Simulation
Discover sampling distributions, Central Limit Theorem, and confidence intervals
🎓 Integration Tips for Instructors
Before Class
Assign relevant module as "flipped classroom" prep—students explore concepts before lecture
During Class
Display module on projector and work through it together, discussing discoveries
After Class
Use modules as review tools or practice assignments
Assessment
Reference module scenarios in quiz questions to test transfer
Student Feedback
Modules are self-paced—great for diverse learning speeds
✨ Why Interactive Modules Work
Learning Benefits
✓ Discovery learning builds deeper understanding than passive reading
✓ Immediate feedback helps students self-correct misconceptions
✓ Visual representations make abstract concepts concrete
✓ Gamified elements increase engagement and motivation
✓ Students can experiment freely without consequences
✓ Self-paced format accommodates diverse learning speeds
📋 Module Overview Table
| Module Series | # Modules | Topic | Best For |
|---|---|---|---|
| Normality | 5 | Assumption checking | Before first analysis |
| Regression | 4 | Predictive modeling | Regression unit |
| Chi-Square | 1 | Categorical data | Chi-square unit |
| Coffee Sim | 1 | Sampling distributions | Intro to inference |
🔗 Quick Links
All modules are:
- Browser-based (no installation needed)
- Mobile-friendly
- Free and open-source
- Hosted on GitHub Pages
Ready to explore? → Visit Module Library