Linear Regression in R for Public Health and Psychology
What You'll Learn
- Describe when a linear regression model is appropriate to use
- Read in and check a data set's variables using the software R prior to undertaking a model analysis
- Fit a multiple linear regression model with interactions, check model assumptions and interpret the output
Course Sections and Titles
1.
Introduction to Linear Regression
2.
Pearson's Correlation Part I
3.
Pearson's Correlation Part II
4.
Intro to Linear Regression: Part I
5.
Intro to Linear Regression: Part II
6.
Linear Regression and Model Assumptions: Part I
7.
Linear Regression and Model Assumptions: Part II
8.
Data Set and Glossary
9.
Linear Regression Models: Behind the Headlines
10.
Warnings and Precautions for Pearson's Correlation
11.
Introduction to Spearman Correlation
12.
Linear Regression in R
13.
Fitting the Linear Regression
14.
Multiple Regression
15.
Assessing Distributions and Calculating the Correlation Coefficient in R
16.
How to Fit a Regression Model in R
17.
Fitting the Multiple Regression in R
18.
Summarising Correlation and Linear Regression
19.
Multiple Regression and Interaction
20.
Model Building