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# The Linear Regression Equation

Linear regression is a way to model the relationship between two variables. You might also recognize the equation as the slope formula. The equation has the form Y= a + bX, where Y is the dependent variable (that’s the variable that goes on the Y axis), X is the independent variable (i.e. it is plotted on the X axis), b is the slope of the line and a is the y-intercept.

The first step in finding a linear regression equation is to determine if there is a relationship between the two variables. This is often a judgment call for the researcher. You’ll also need a list of your data in x-y format (i.e. two columns of data—independent and dependent variables).

Warnings:

1. Just because two variables are related, it does not mean that one causes the other. For example, although there is a relationship between high GRE scores and better performance in grad school, it doesn’t mean that high GRE scores cause good grad school performance.
2. If you attempt to try and find a linear regression equation for a set of data (especially through an automated program like Excel or a TI-83), you will find one, but it does not necessarily mean the equation is a good fit for your data. One technique is to make a scatter plot first, to see if the data roughly fits a line before you try to find a linear regression equation.