Multiple Regression

Question 1

The mathematical equation relating the expected value of the dependent variable to the value of the independent variables, which has the form of E(y) = B0 + B1x1+…+Bp x p is

Answer 1

a multiple regression equation

Question 2

The mathematical equation that explains how the dependent variable y is related to several independent variables x1, x2, …, xp and the error term ‘sum’ is

Answer 2

a multiple regression model

Question 3

A multiple regression model has

Answer 3

more than one independent variable

Question 4

A regression model in which more than one independent variable is used to predict the dependent variable is called

Answer 4

a multiple regression model

Question 5

A multiple regression model has the form
Yhat =5+6X+7W
As X increases by 1 unit (holding W constant), Y is expected to

Answer 5

increase by 6 units

Question 6

A measure of goodness of fit for the estimated regression equation is the

Answer 6

multiple coefficient of determination

Question 7

The adjusted multiple coefficient of determination is adjusted for

Answer 7

the number of independent variables

Question 8

In a multiple regression analysis involving 15 independent variables and 200 observations, SST = 800 and SSE = 240. The coefficient of determination is

Answer 8

0.700

Question 9

The correct relationship between SST, SSR, and SSE is given by

Answer 9

SSR = SST - SSE

Question 10

In a multiple regression analysis involving 10 independent variables and 81 observations, SST = 120 and SSE = 42. The coefficient of determination is

Answer 10

0.65

Question 11

In a multiple regression analysis involving 5 independent variables and 30 observations, SSR = 360 and SSE = 40. The coefficient of determination is

Answer 11

0.90

Question 12

In a multiple regression model, the error term  is assumed to be a random variable with a mean of

Answer 12

zero

Question 13

In a multiple regression model, the values of the error term ,’sum’, are assumed to be

Answer 13

independent of each other

Question 14

In order to test for the significance of a regression model involving 3 independent variables and 47 observations, the numerator and denominator degrees of freedom (respectively) for the critical value of F are

Answer 14

3 and 43

Question 15

A term used to describe the case when the independent variables in a multiple regression model are correlated is

Answer 15

multicollinearity

Question 16

A regression model involved 5 independent variables and 136 observations. The critical value of t for testing the significance of each of the independent variable’s coefficients will have

Answer 16

130 degrees of freedom

Question 17

The ratio of MSE/MSR yields

Answer 17

not SST, the F statistic nor SSR

Question 18

In order to test for the significance of a regression model involving 14 independent variables and 255 observations, the numerator and denominator degrees of freedom (respectively) for the critical value of F are

Answer 18

14 and 240

Question 19

In order to test for the significance of a regression model involving 8 independent variables and 121 observations, the numerator and denominator degrees of freedom (respectively) for the critical value of F are

Answer 19

8 and 112

Question 20

In order to test for the significance of a regression model involving 4 independent variables and 36 observations, the numerator and denominator degrees of freedom (respectively) for the critical value of F are

Answer 20

4 and 31