Chapter 1: What is linear regression?

The main purpose of linear regression analysis is to assess associations between dependent and independent variables. In this chapter, you will learn the basic idea behind this technique. You will also learn how to create a graphic presentation of the association between two variables by means of a regression line.

Strictly speaking, linear regression requires variables to be metric. Non-metric variables are either nominal or ordinal. The ESS data abound with ordinal variables, such as measurements of opinions. This creates problems for the application of linear regression analysis to ESS data. Some of these problems may be alleviated. We deal with this in later chapters. For now, it suffices to say that, in addition to metric variables, all variables that have no more than two values may be used as independent variables in linear regression analyses. This is illustrated in the following example.