Error degrees of freedom are calculated as n - p - 1 for multiple regression models. the p represents the number of coefficients (not including the intercept) in the estimated model. part a: report the error degrees of freedom for this example: assume 160 observations are used to estimate a model with 2 numerical explanatory variables both with a linear relationship to the response and 1 categorical explanatory variable. the categorical variable has 4 levels. part b: assume 160 observations are used to estimate a model with 2 numerical explanatory variables both with a linear relationship to the response. in addition there is one categorical variable with 3 levels and another categorical variable with 4 levels. report the error degrees of freedom

Part (A) The Error Degrees of Freedom for this example is 154.

Part (B) The Error Degrees of Freedom for this example is 152.

Step-by-step explanation:

Consider the provided information.

The categorical variable has 4 levels.

It is given that 160 observations are used to estimate a model with 2 numerical explanatory variables both with a linear relationship to the response and 1 categorical explanatory variable.

Thus, the total number of coefficients(p) = 2+(4-1)=5

It is given that Error Degrees of Freedom are calculated as n - p - 1

Substitute n = 160 and p=5  in above formula.

Hence, the Error Degrees of Freedom for this example is 154.

Part B: Categorical variable with 3 levels and another categorical variable with 4 levels. Also a model with 2 numerical explanatory variables both with a linear relationship to the response.

Thus, the total number of coefficients(p) = 2+(3-1)+(4-1)=7

It is given that Error Degrees of Freedom are calculated as n - p - 1

Substitute n = 160 and p=5  in above formula.

Hence, the Error Degrees of Freedom for this example is 152.

it’s supposed to be -4+45=41

step-by-step explanation: