ABSTRACT
I am fi ve feet six inches tall. And proud! The average height of the American male is fi ve feet nine inches, so I am a bit on the shorter side, but not dramatically so. Occasionally, I experience what I consider to be discrimination, but these are minor occurrences, such as when clothing store sizes start at “M” instead of “S.” So imagine my absolute horror when I heard that studies had found a very serious form of discrimination: shorter men actually make less money than do taller men. I thought that this would be a good example to start our exploration of simple regression , as the variables involved are so very visual: you can see when someone’s short or tall, and you can see when someone’s poor or rich. These are also good variables because both of them are measured at the ratio level. Regression in its simple form is bivariate,
involving two ratio-level variables that are related to one another in a linear fashion. One of these variables serves as the independent variable, and the other serves as the dependent variable.
