Chapter 15: Multiple Regression

A regression model in which more than one independent variable is used to predict the dependent variable is called
1. a simple linear regression model
2. a multiple regression model
3. an independent model
4. none of the above
A term used to describe the case when the independent variables in a multiple regression model are correlated is
1. regression
2. correlation
3. multicollinearity
4. none of the above
A multiple regression model has the form: y = 2 + 3x1 + 4x2. As x1 increases by 1 unit (holding x2 constant), y will
1. increase by 3 units
2. decrease by 3 units
3. increase by 4 units
4. decrease by 4 units
A multiple regression model has
1. only one independent variable
2. more than one dependent variable
3. more than one independent variable
4. none of the above
A measure of goodness of fit for the estimated regression equation is the
1. multiple coefficient of determination
2. mean square due to error
3. mean square due to regression
4. none of the above
The adjusted multiple coefficient of determination accounts for
1. the number of dependent variables in the model
2. the number of independent variables in the model
3. unusually large predictors
4. none of the above
The multiple coefficient of determination is computed by
1. dividing SSR by SST
2. dividing SST by SSR
3. dividing SST by SSE
4. none of the above
For a multiple regression model, SST = 200 and SSE = 50. The multiple coefficient of determination is
1. 0.25
2. 4.00
3. 0.75
4. none of the above
The correct relationship between SST, SSR, and SSE is given by
1. SSR = SST + SSE
2. SST = SSR + SSE
3. SSE = SSR - SST
4. all of the above
5. none of the above
The ratio of MSR/MSE yields
1. the t statistic
2. SST
3. the F statistic
4. none of the above

Chapter 15: Multiple Regression

Quiz