- Week 1 (9/6):
- Questionnaire
- Introduction to the course
- Why use models?
- Homework:
- Week 2 (9/11, 9/13):
- Introduction to R, RStudio, and R Markdown lab
- Understanding statistical models
- Four Step process
- Homework:
- Read Ch. 1
- HW #1 due Monday Sept 17 by 11:55 pm, submit on Canvas
- Week 3 (9/18, 9/20):
- Residuals lab
- Assessing Conditions
- Making Predictions
- Transformations lab
- Outliers and Influential Points
- Homework:
- Read Ch. 2
- HW #2 due Monday Sept 24 by 11:55 pm, submit to Canvas
- Week 4 (9/25, 9/27):
- Inference for the Slope Coefficient
- ANOVA
- Regression and Correlation
- Intervals and data wrangling lab
- Homework:
- Read selection from Modern Data Science with R
- HW #3 due Monday, October 1 by 11:55 pm, submit to Canvas
- Week 5 (10/2, 10/4):
- Multiple Linear Regression
- Assessing Conditions in MLR
- Comparing two models
- Homework:
- Read Ch. 3.1 - 3.3
- HW #4 due Monday, October 8 by 11:59 pm, submit to Canvas
- Week 6 (10/9, 10/11)
- Interaction terms
- Multicollinearity
- Putting it all together
- Homework:
- Project groups due by Monday, 10/15
- Read Ch. 3.4 - 3.8
- No homework problems, exam Tuesday
- Week 7 (10/16, 10/18)
- EXAM 1 Tuesday
- Interpreting nested F-tests
- Polynomial regression
- Stepwise Regression
- Homework:
- Read Ch. 4.2 - 4.4 (skipping 4.1)