One of the most common things in statistics is to describe the linear relationship between two variables by fitting a best-fit line to the scatterplot of those variables. The method for finding the best-fit line is called simple linear regression and is the topic of this module.
After completing this module, you should be able to ...
- Describe the purposes of regression.
- Describe the criteria used to determine the best-fit line to a set of bivariate data.
- Describe the assumptions surrounding the best-fit criteria.
- Identify the response and explanatory variables.
- Describe the equation of a line and what the slope and intercept "mean."
- Make appropriate predictions using the best-fit line.
- Describe the meaning of the coefficient of determination.
Preparation for Class
Use the resources below to answer these questions. [Problems with videos?]
- Primary Resources (13 pages, 73 mins)
- Reading
R-Squared [5 mins] … corresponding slides- Regression Questions [10 mins] … corresponding slides
- Assumptions [3 mins] … corresponding slides
- Fall 2020B In-Class “Review Lecture” [55 mins]
- Projection is this example
- Projection is this example
- Secondary Resources
Response and Explanatory Variables I [1 min; between 1:00 and 2:28]- Response and Explanatory Variables II [6 mins; stop at 6:18]
- Introduction to Regression [14 mins]
Practice
Archive
- Exercises