Unit 6: Linear Regression

In this unit, we will discuss situations where the mean of a population, treated as a variable, depends on the value of another variable. One of the main reasons we conduct such analyses is to understand how two variables are related. The most common type of relationship is a linear relationship. For example, you may want to know what happens to one variable when you increase or decrease the other variable. You want to answer questions such as, "Does one variable increase as the other increases, or does the variable decrease?" For example, you may want to determine how the mean reaction time of rats depends on the amount of drug in the bloodstream.

You will also learn to measure the degree of a relationship between two or more variables. Both correlation and regression are measures for comparing variables. Correlation quantifies the strength of a relationship between two variables and is a measure of existing data. On the other hand, regression is the study of the strength of a linear relationship between an independent and dependent variable. It can be used to predict the value of the dependent variable when the value of the independent variable is known.

Completing this unit should take you approximately 3 hours.