Class Data Demos on Google Sheets
Complete assigned readings before next class meeting, which are yellow-highlighted.
DA13a Team Project Presentation: PPT
DA13b Logistic Regression: PPT
- Example Study: In a Job Interview, How Much does Timing Matter? (No Stupid Question Podcast)
- Multiple Regression chapter, Statistical Analysis in JASP - A Guide for Students (starting page 54)
- DA Worksheet #14: Logistic Regression (solution; Python Solution)
- Multiple Regression by Dr. Josh Starmer
- Reading: Multiple Linear Regression Model & Evaluation
DA14 Multiple Regression: PPT
- DA Worksheet #15: Multiple Regression (solution)
- ROC & AUC (Wilber, Amazon Machine Learning University)
- Equality of Odds (Wilber, Amazon Machine Learning University)
- Reading: Transformation & Interaction
- Reading: Influential Points (Outliers)
- Reading: Regression Pitfalls
- Reading: Categorical Predictors
- Reading: Transformation & Interaction
- Reading: Nonlinear Regression
- Khan Academy module on Non-Linear Regression
- Reading: 18 Types of Regression and When to Use them
[Optional] Time Series Analysis: PPT
- HA Chapter 5: Forecasting Principles and Practice by Hyndman & Athanasopoulos
- DA Worksheet #16: Time Series Analysis (Solution)
- Time Series Analysis by Jordan Kern
- Time Series Modeling by Jordan Kern
*Access Harvard Business Review through the William & Mary Library proxy