Full Answer
estimated regression equation, in statistics, an equation constructed to model the relationship between dependent and independent variables. Either a simple or multiple regression model is initially posed as a hypothesis concerning the relationship among the dependent and independent variables.
The estimated regression equations show the equation for y hat i.e. predicted y. The regression model on the other hand shows equation for the actual y. This is an abstract model and uses population terms (which are specified in Greek symbols).
In case of just one x variable the equation would like this: b0 is the constant (also called line intercept). b1 is the slope of the regression line for the x1 variable. Note that we use “y hat” as opposed to “y”. Y hat signifies predicted y value, where as “y” signifies actual y value.
How to write estimated regression equation from SPSS output: For this you need to refer to the Coefficients table as shown in the SPSS regression output. Here we have two x variables that’s why the estimated regression equation looks like: In case of just one x variable the equation would like this: b0 is the constant (also called line intercept).