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Eberly College of Science
STAT 462
Applied Regression Analysis
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Welcome to STAT 462!
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Lessons
Lesson 1: Statistical Inference Foundations
Lesson 2: Simple Linear Regression (SLR) Model
Lesson 3: SLR Evaluation
Lesson 4: SLR Assumptions, Estimation & Prediction
Lesson 5: Multiple Linear Regression (MLR) Model & Evaluation
Lesson 6: MLR Assumptions, Estimation & Prediction
Lesson 7: Transformations & Interactions
Lesson 8: Categorical Predictors
Lesson 9: Influential Points
Lesson 10: Regression Pitfalls
Lesson 11: Model Building
Lesson 12: Logistic, Poisson & Nonlinear Regression
Resources
Website for Applied Regression Modeling, 2nd edition
Notation Used in this Course
R Software Help
Minitab Software Help
