This edition: Inference for Regression
This lesson returns to the topic of regression introduced in Lessons 5 and 6. While researchers benefit from knowing the correlation between two variables, they also want to be able to apply the same inferences to a correlation as they do for other quantitative measures, such as the mean. It’s often possible to see the correlation between two quantitative variables in a scatterplot, but, in addition, researchers want to make estimates for the population as a whole just as they do when they estimate population means and proportions.
Making inferences about the correlation of variables from a scatterplot requires yet another statistical test, a test that has a distribution you have seen before and that is based on some new assumptions about the correlation. This test gives us the ability to estimate the correlation in the population with a certain amount of confidence, and is yet another important tool statisticians use. In this lesson, you’ll see how this test is applied to the relationship between a pesticide and eggshell thickness to determine if a species is able to survive or not. The answer to that question comes from testing the linear relationship between two important quantitative variables.