![]() Linear regression can be visualized by a line of best fit through a scatter plot, with the dependent variable on the y axis. Each extra unit of size is associated with a $20 increase in the price of the house, controlling for the age and the number of rooms. This model would be created from a data set of house prices, with the size, age and number of rooms as independent variables. Price of House = 0 + 20 * size – 5 * age + 2 * rooms To give a concrete example of this, consider the following regression: Multiple regression finds the relationship between the dependent variable and each independent variable, while controlling for all other variables. ![]() The coefficients can be different from the coefficients you would get if you ran a univariate regression for each factor. Where y is the dependent variable, x i is the independent variable, and β i is the coefficient for the independent variable. ![]()
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June 2023
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