Statistics Review

STAT 155 Notes: https://mac-stat.github.io/Stat155Notes/

Key Concepts

• Multiple Linear & Logistic Regression Models
  • Model Equations
  • Coefficient Interpretation
  • Multicollinearity
  • Interaction, Indicators
  • Model Selection
• Sampling Variability
  • Expected Value
  • Standard Deviation
  • Sampling Distribution
  • Standard Error (estimate of Standard Deviation)
• Statistical Inference
  • Hypothesis Testing (Null, Statistic, P-value)
  • Confidence Interval
  • Inference in Regression Models
    • Individual Slopes (t-tests)
    • Nested Models (F-tests)

STAT 253 Materials: https://bcheggeseth.github.io/253_spring_2025/

Key Concepts

• Non-linear parametric modeling
  • Polynomial regression
  • Spline regression
• Comparison and Justification of Models
  • Considering Pros and Cons
  • Model Evaluation Questions
    • Is it good? Is it wrong? (assumptions valid?)
    • Is predict accurately (focus of 253)?
    • Is it strong? (how much variation is explained)
    • Is it fair? (benefits and harms)