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 In Statistical modeling, regression analysis is a set of statistical processes to estimate the relationship between a dependent variable (often referred to as the 'outcome variable') and one or more independent variables (often referred to as 'predictors,' 'covariates' or 'functions'). Linear regression is the most common method of regression analysis, where a researcher seeks the line (or a more complex linear combination) that most closely matches the data according to a certain mathematical criterion. For instance, the ordinary least squares method calculates the unique line (or hyperplane) which minimizes the sum of square distances between the true data and that line (or hyperplane).

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