• Sources of Variation in an Experiment
  • Exploration 1.1: Sand Crabs
• Quantifying Sources of Variation
  • Exploration 1.2 – 1.3: Starry navigation
• Comparing Several Groups
  • Exploration 1.4 – 1.5: Golden Squirrels
• More Study Design Considerations
  • Exploration 1.6: Cholesterol levels and living altitude
• Paired Data
  • Exploration 2.1: Finch songs
• Randomized Complete Block Designs
  • Exploration 2.2: How does caffeine affect finger tapping?
• Multi-factor Studies and Interactions
  • Exploration 3.1: Pig growth
• Statistical Interactions
  • Exploration 3.2: What determines a baby skink’s weight?
• Simple Linear Regression with Single Quantitative Explanatory Variable
  • Exploration 4.1 – 4.2: Fatty Acids and DNA
• Regression Models with Both Categorical and Quantitative Explanatory Variables
  • Exploration 4.3: Predicting Blood Glucose
• Quantitative/Categorical Interactions
  • Exploration 4.4: FEV and smoking
• Experiments with Multiple Quantitative Explanatory Variables
  • Exploration 5.1: Biodiesel
• Nonlinear Models: Polynomial Functions
  • Exploration 5.3: Predicting Skeletal Mass from Humerous Length in Birds
• Comparing Proportions
  • Exploration 6.1: Give Peas a Chance
• Simple Logistic Regression
  • Exploration 6.2: Horseshoe Crabs
• Logistic Regression with Multiple Explanatory Variables
  • Exploration 6.3: Predicting Breast Cancer