Summary and Final Tasks

Summary

In Lesson 8, you have learned about applying linear regression to a dataset. Linear regression allows one to quantitatively asses the relationship between two quantitative variables. One can use such an identified relationship to make predictions of the response variable, given a value of the explanatory variable. Lesson 8 is generally ordered by the tasks that one would want to perform in doing linear regression:

Measure and Test for Correlation and Slope: if there is little to no linear relationship between the two variables, there is no point in proceeding further.
Measure Goodness-of-Fit: Does a linear model fit well? Does it explain the majority of variability in the response? If so, what do you learn about the problem by examination of the slope and intercept?
Make Predictions: Just the prediction alone is not very useful, so make sure to also examine the prediction interval to understand the range of possible values that may arise.

We also covered some transformations that you may need to perform to apply linear regression to your dataset.

Assess it: Check Your Knowledge Quiz

Reminder - Complete all of the Lesson 8 tasks!

You have reached the end of Lesson 8! Double-check the to-do list on the Lesson 8 Overview page [1] to make sure you have completed all of the activities listed there before you begin Lesson 9.