For a layman what is linear regression?
Sep 5, 2018 1,277 views

Linear regression is a statistical technique to predict the value of y based on some value  input value x, after recognizing the relationship among the variables y and x.

General formula for a linear regression is y = m1x1 + m2x2+m3x3+....+c. Where in x1, x2, x3,... are the input variables.

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Linear regression is a basic and commonly used type of predictive analysis.  The overall idea of regression is to examine two things: (1) does a set of predictor variables do a good job in predicting an outcome (dependent) variable?  (2) Which variables in particular are significant predictors of the outcome variable, and in what way do they–indicated by the magnitude and sign of the beta estimates–impact the outcome variable?  These regression estimates are used to explain the relationship between one dependent variable and one or more independent variables.  The simplest form of the regression equation with one dependent and one independent variable is defined by the formula y = c + b*x, where y = estimated dependent variable score, c = constant, b = regression coefficient, and x = score on the independent variable.

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linear regression is useful for finding relationship between two continuous variables. One is predictor or independent variable and other is response or dependent variable. It looks for statistical relationship but not deterministic relationship. Relationship between two variables is said to be deterministic if one variable can be accurately expressed by the other.
answered Aug 7, 2019 by nikita

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