# Week 4: Multiple Linear Regression

## January 29-30, 2018

The logic behind multiple linear regression is similar to that of simple regression. This week we will look at what happens when you regress more than one covariate against Y.

We will focus on running and interpreting these models, but will not look at assessing their fit just yet. (We will save that for Week 5).

### Lecture Topics

- The basic structure of a general linear model
- How to interpret beta values for categorical and continuous covariates
- Interation terms
- Specifying models in lm()

### In-class Activities

Part 1 will involve some relatively simple code, but perhaps complicated concepts. Part 2 will be more hands-on, and there will be a larger exercise as we work on the data from the lionfish paper below.

### Pre-class Prep

**Optional**

In Part 1, we will look at urchin data from the paper we worked on in week 2. In Part 2, we will use data from the paper below:

You may read if interested.

### Files

Note: This only contains Part 1 content as of Jan 26. Will update with Part 2 by end of day Jan 29.

### Slides

Part 1 slides via speakerdeck

Part 2 slides via speakerdeck