Tag Archives: regression

Statistics: Choosing a Test

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The following post is about breaking down the uses for different types of tests. More importantly, it’s designed to help you know what test to use based on the question being asked. This is not a comprehensive list of all the statistical tests out there, so if you feel that there is something missing which you would like to be included, please leave a comment below. All formulas for the tests presented here can be found in the Statistics Formula Glossary post. At the bottom is a decision tree which may be helpful in visualizing the purpose of this post. Continue reading →

Statistics: Regression

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Introduction to Linear Regression

Linear regression is a method for determining the best-fitting line through a set of data. In a lot of ways, it’s similar to a correlation since things like r and r squared are still used. The one difference is that the purpose of regression is prediction. The best-fitting line is calculated through the minimization of total squared error between the data points and the line.

The equation used for regression is Y = a +bx or some variation of that. If you remember from algebra class, this formula is like Y=mx+b. This is because they are both the linear equation. Although you may be asked to report r and r squared, the purpose of regression is to be able to find values for the slope (b) and the y-intercept (a) that creates a line that best fits through the data. Continue reading →