| Items |
|---|
| Fit a linear regression model with multiple predictors and interpret the coefficients |
| Interpret the regression coefficient for binary, and categorical predictors |
| Fit a model with a log transformed, or binary outcome and interpret the results |
| Choose the best fitting model among several candidates using metrics like R2, AIC, BIC and Accuracy |
Multiple & Generalized Regression
Because life isn’t bivariate
Learning Path
Where we’ve been
Learning how a third variable can modify the relationship between two explanatory and response variables.
Where we’re at
Learning how to expand regression models to include more than 1 predictor, and how to fit other non-linear regression models.
Objectives
Learning Materials
Slides (Will open in full screen. Right click to open in a new tab)
📚 Reading
| Items |
|---|
| Topic Overview |
| PMA6 Ch 12 |
| ASCN 10.5 |
| ASCN 10.2.1, ASCN 10.4 Intro, ASCN 10.3 |
| PMA6 Ch 8 |
| A blog about statistical musings |
| How to control confounding effects by statistical analysis |
Assignments
| Items |
|---|
| HW09 |
| in class jigsaw lecture |