![]() ![]() That said, too many variables will not improve the model and in some cases hurt it. You can add any number of independent variables with a coefficient attached to each to see the impact each has on the dependent variable.In order to do this, you take the existing data that you have and test all of the cases against this equation to find the most appropriate a and b in order to predict y values that you don’t have data for. It’s a way of figuring out the impact the independent variable x has on the dependent variable y.The equation is in the format: y=ax+b, where y is the dependent variable, x is the independent variable, a is a coefficient, and b is a constant/y-intercept.What I know about linear regression going into the weekend: Part I | My scope of knowledge upon beginning to write this postįirst, to establish grounds, let me tell you what I do know about regression, and what I can do in R. Part V | Next steps: Improving your model. ![]()
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