multiply linear regression model
A multiple linear regression model is a statistical model that analyzes the relationship between multiple independent variables and a dependent variable. It is an extension of simple linear regression, which only considers one independent variable.
The model assumes that the relationship between the dependent variable and independent variables is linear. The model is expressed as:
Y = β0 + β1X1 + β2X2 + ... + βnXn + ε
Where Y is the dependent variable, X1, X2, ..., Xn are the independent variables, β0 is the intercept, β1, β2, ..., βn are the coefficients of the independent variables, and ε is the error term.
The coefficients (β1, β2, ..., βn) represent the change in the dependent variable for a one-unit change in the corresponding independent variable, holding all other independent variables constant.
The model can be used to predict the value of the dependent variable for a given set of independent variables. The accuracy of the model can be assessed using measures such as R-squared, adjusted R-squared, and root mean squared error (RMSE)
原文地址: https://www.cveoy.top/t/topic/fiYY 著作权归作者所有。请勿转载和采集!