# Analyzing Continuous Data

In this unit, you will become familiar with running and plotting correlations and regression in R.

Follow the links to each lecture, lab, and reading.

Scroll down to download the SWIRL lessons.

## Lesson 1. How to test for correlation and causation

Lecture: Testing associations

Learning Goals:

- Run correlation and simple regression models,
- Interpret output,
- Extract and plot details from output.

SWIRL: Testing_Associations

Lab: Unit 4: Lab 1

Reading: Crawley, M. The R Book. Ch 10 Regression.

Functions: `ks.test()`

, `cor()`

, `lm()`

, `abline()`

, `coef()`

.

## Lesson 2. How to work with multiple predictors

Lecture: Multiple regression

Learning Goals:

- Understand how to code different statistical relationships,
- Interpret model output and diagnose model fit.

SWIRL: Testing_Associations

Lab: Unit 4: Lab 2

Reading: Crawley, M. The R Book. Ch 12. Analysis of Covariance.

Functions:

## Lesson 3. How to deal with binomial and count data

Lecture:

Learning Goals:

- Understand binomial and count data,
- Know how to analyse and plot these data,
- Extract, predict, and plot these data.

SWIRL:

Lab: Unit 4: Lab 3

Reading: Crawley, M. The R Book. Chs 13–17.

Functions: `glm()`

, `predict()`

, `lines()`

.

## Lesson 4. How to modify standard plots

Lecture: Modifying plots

Best Practice: Principles of graphic design

Learning Goals:

- Be able to select and justify the choice of data presentation,
- Understand principles of best practice in figure design,
- Modify default graphs,
- Search for help.

SWIRL: Modifying default graphs

Exercises: Unit 4 Exercises

Lab: Unit 4: Recap

Reading: Chart Chooser

Functions: `plot()`

, `par()`

,