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Welcome to Statistics for Behavioral/Natural Science 224

Curated Stats 224 Doc

This comprehensive documentation provides everything you need for Statistics for Behavioral/Natural Science 224, from fundamental concepts to advanced statistical analyses.

🚀 Quick Navigation

First Time Here?

→ Start with Getting Started
→ Set up R and Posit Cloud
→ Try the Interactive Modules

Need to Run a Statistical Test?

→ Use the Decision Tree to find the right test
→ Check Common Scenarios for examples
→ Jump to the specific test workflow

Checking Assumptions?

→ See Understanding Normality
→ Check Assumption workflows
→ Learn about Effect Sizes

Need Practice?

→ Explore Interactive Learning Modules
→ Try the Normality Series
→ Work through Regression Modules

📚 Main Sections

Assumptions & Diagnostics

Essential assumption checking:

  • Understanding Normality - Conceptual foundation
  • Checking Normality - Practical workflows
  • Other Assumptions - Independence, homogeneity, linearity
  • When Assumptions Fail - Transformations and alternatives

Parametric Tests

Complete workflows for:

  • T-Tests: One-sample, Independent, Paired
  • ANOVA: One-way, Two-way, Repeated Measures
  • Regression: Simple, Multiple, Diagnostics

Non-Parametric Tests

Alternatives when assumptions fail:

  • Mann-Whitney U Test
  • Kruskal-Wallis Test
  • Wilcoxon Signed-Rank Test

Chi-Square Analysis

For categorical data:

  • Test of Independence
  • Goodness of Fit Test

🎓 Interactive Learning

11+ Browser-Based Modules

Normality Series (5 modules)
Master assumption checking through progressive learning

Regression Series (4 modules)
Build intuition with dynamic visualizations

Chi-Square & Probability
Hands-on categorical data analysis and sampling distributions

Visit Module Library →

📊 Key Features

What Makes This Documentation Special

✓ Definitive Workflows - One authoritative guide per test
✓ Decision Trees - Visual guides for test selection
✓ Effect Size Reference - Interpretation at your fingertips
✓ Code Examples - Copy-paste R workflows
✓ Troubleshooting - Real error messages with solutions
✓ Interactive Modules - Hands-on learning tools
✓ Reporting Templates - APA-style examples

🔍 How to Use This Documentation

For Quick Reference

Use the search bar above to find any topic instantly

For Learning

Follow the sections in order, working through examples

For Analysis

  1. Which Test? - Choose your test
  2. Navigate to that test's workflow
  3. Copy and adapt the R code
  4. Check Effect Sizes for interpretation

For Teaching

📖 About This Documentation

Course: Statistics for Behavioral/Natural Science 224
Institution: Columbia College of Missouri
Author: Jon Oxford, Ph.D. (Herr Prof. Dr. Awesome-Sauce)

This documentation integrates:

  • Comprehensive statistical theory
  • Practical R workflows
  • Interactive learning modules
  • Professional best practices

Last Updated: November 2025

🆘 Need Help?

  • Can't find a topic? Use the search bar above
  • Unsure which test? Try the Decision Tree
  • Assumptions failing? See test-specific troubleshooting sections
  • Want practice? Explore Interactive Modules

Pro Tip

Bookmark this page! You'll reference it frequently throughout the course.

Ready to begin? → Get Started