Multiple Linear Regression Model. Multiple linear regression the population model in a simple linear regression model a single response measurement y is related to a single predictor covariate regressor x for each observation. Y the predicted value of the dependent variable b0 the y intercept value of y when all other parameters are set to 0 b1x1 the regression coefficient b 1 of the first independent variable x1 a k a.
Do. Y the predicted value of the dependent variable b0 the y intercept value of y when all other parameters are set to 0 b1x1 the regression coefficient b 1 of the first independent variable x1 a k a. The multiple regression model is based on the following assumptions.
The independent variables are not too highly correlated with each other.
That is we use the adjective simple to denote that our model has only predictor and we use the adjective multiple to indicate that our model has at least two predictors. That is we use the adjective simple to denote that our model has only predictor and we use the adjective multiple to indicate that our model has at least two predictors. There is a linear relationship between the dependent variables and the independent variables. The critical assumption of the model is that the conditional mean function is linear.
