![]() The most common form of regression analysis is linear regression, in which one finds the line (or a more complex linear combination) that most closely fits the data according to a specific mathematical criterion. In statistical modeling, regression analysis is a set of statistical processes for estimating the relationships between a dependent variable (often called the 'outcome' or 'response' variable, or a 'label' in machine learning parlance) and one or more independent variables (often called 'predictors', 'covariates', 'explanatory variables' or 'features'). Thus for X=6 we forecast Y=3.2, and for X=7 we forecast Y=3.Set of statistical processes for estimating the relationships among variables Regression line for 50 random points in a Gaussian distribution around the line y=1.5x+2 (not shown) Part of a series on
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