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Simple linear regression uses one independent variable to predict one dependent variable. Multiple linear regression uses two or more independent variables to predict a dependent variable.
In the example below, I use an e-commerce data set to build a regression model. I also explain how to determine if the model reveals anything statistically significant, as well as how outliers may ...
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How-To Geek on MSNThis Python Code Could Save You From Spending Too Much on Your Next LaptopYou could sift through websites, but some Python code and a little linear regression could make the job easier. ...
Sometimes, a model uses the square, square-root or any other power of one or more independent variables to predict the dependent one, which makes it a non-linear regression.
How Homoskedasticity Works Homoskedasticity is one assumption of linear regression modeling, and data of this type work well with the least squares method.
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