Module 2: Linear Regression

Topic: Simple and multiple linear regression, residuals, predictions, R², F-statistics, interactions.

Learning Objectives

Fit linear models with lm()
Interpret coefficients, R², and F-statistics
Visualize regression lines and residuals
Understand interaction terms

Slides

Linear Regression 1 (PDF)

R Code

Data

Key Packages

library(ggplot2)
library(plotly)

Assignment

HW2: Linear Regression — due Module 3 Wednesday. Submit on Canvas.

---
title: "Module 2: Linear Regression"
---

::: {.week-header}
**Topic:** Simple and multiple linear regression, residuals, predictions, R², F-statistics, interactions.
:::

## Learning Objectives

- Fit linear models with `lm()`
- Interpret coefficients, R², and F-statistics
- Visualize regression lines and residuals
- Understand interaction terms

## Slides

::: {.file-list}
- [Linear Regression 1 (PDF)](../Week%202/Linear%20Regression%201.pdf)
:::

## R Code

::: {.file-list}
- [Linear Regression 1.R](../Week%202/Linear%20Regression%201.R)
- [Linear Regression 2.R](../Week%202/Linear%20Regression%202.R)
:::

## Data

::: {.file-list}
- [wheat.csv](../Week%202/wheat.csv)
- [birds.csv](../Week%202/birds.csv)
:::

## Key Packages

```r
library(ggplot2)
library(plotly)
```

## Assignment

**HW2: Linear Regression** — due Module 3 Wednesday. Submit on Canvas.