Regression is a statistical measure used that attempts to determine the strength of the relationship between one dependent variable and a series of other changing (independent) variables. The two basic types of regression are linear regression and multiple linear regression, although there are non-linear regression methods for more complicated data and analysis. Linear regression uses one independent variable to explain or predict the outcome of the dependent variable, while multiple regression uses two or more independent variables to predict the outcome. Regression can help predict sales for a company based on weather, previous sales, GDP growth or other conditions. Regression takes a group of random variables and tries to find a mathematical relationship between them. This relationship is typically in the form of a straight line (linear regression) that best approximates all the individual data points.

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If you want to look for more information, check some free online courses available at coursera.org, edx.org or udemy.com.

Recommended reading list:

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