On Monday, we will practice fitting nonlinear curves. The in-class case study is on finding an optimal price for milk, given historical sales and price data. This will finish out Chapter 2 of the course packet. You might also want to check out the mini walkthrough on how to optimize a function in R.
On Wednesday, we will learn to quantify forecasting error using prediction intervals. We will also learn about the decomposition of variance. This material comes from chapter 3 of the course packet.
Videos
Please watch the following videos to prepare for next week:
- Introduction to grouping variables in regression.
- Dummy variables.
- Multiple grouping variables: main effects and interactions.
- The analysis of variance.
Software practice
Complete the following software walkthroughs. For Wednesday in class:
- kidney function and aging: naive prediction intervals and the decomposition of variance
For next week:
- reaction time in video games: modeling numerical outcomes with more than one categorical predictor; dummy variables and interaction terms; analysis of variance.
Readings
From the course packet, please read Chapter 3 by Wednesday. For Monday of next week, please read Chapter 4 through page 94 (stopping at the section on “Numerical and grouping variables together.”)
Exercises
The exercises this week are about linear and nonlinear regression. They are due on Monday, February 6 at the beginning of class.