Multiple Regression:

Multiple (linear) regression is a regression technique aimed at finding a linear relationship between the dependent variable and multiple independent variables. (See regression analysis.)

The multiple regression model is as follows:

where Y_i are values of the dependent variable, X_1i, X_2i, ... , X_mi are values of m independent variables, E_i - random errors, N > m+1 is the sample size.

Multiple regression finds the set of parameters B₀, B₁, ... , B_mi that provides the best fit between the model and the given data (which are a set of N vectors - {(Y_i, X_1i, ... , X_mi), i=1,...,N}).

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