# Analyzing Continuous Data

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

## 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: `lm()`

## 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 deal with multiple response variables (multivariate data)

Lecture: Multivariate Data

Learning Goals:

• Understand multivariate data,
• Know how to analyse and plot multivariate data,
• Search for help on multivariate analyses.

More details:

SWIRL: Ordination

Lab: Unit 4: Recap

Functions: `pcord`, `prcomp()`, `princomp()`, `pca()`, `biplot()`, `interp()`.