Exam 14: Multiple Regression and Correlation Analysis

To evaluate the assumption of linearity,a multiple regression analysis should include

What is the range of values for multiple R?

In multiple regression analysis,residuals (Y - Ŷ )are used to:

In multiple regression analysis,a correlation matrix is used to check for _____________.

In a multiple regression analysis,if the regression coefficient of a dummy variable is significant and has a sample value of 100,then the dummy variable's effect on the dependent variable is: no effect,an increase of 100,or a decrease of 100.

What does the multiple standard error of estimate measure?

To evaluate homoscedasticity,we plot the values of for all values of X.

A multiple regression equation defines the relationship between a dependent variable and a set of independent variables in the form of an equation.

The production of automobile tires in any given year is related to the number of automobiles produced this year and in prior years.Suppose our econometric model resulted in the following data. What is the equation for our model? ____________________________

The variance inflation factor is used to select or remove independent variables to reduce the effects of multicollinearity in a multiple regression equation.

A coefficient of multiple determination equaling -0.99 shows that the dependent variable is inversely related to a set of independent variables.

Twenty-one executives in a large corporation were randomly selected for a study to determine the effect of several factors on annual salary (expressed in $000's).The factors selected were age,seniority,years of college,number of company divisions they had been exposed to and the level of their responsibility.A regression analysis was performed using a popular spreadsheet program with the following regression output: If other variables are held constant,how does an increase in age of two years affect salary? _________________

What statistic is used to assess multicollinearity in multiple regression analysis?

The following correlations were computed as part of a multiple regression analysis that used education,job,and age to predict income. Which independent variable has the weakest association with the dependent variable?

If the correlation between the two independent variables of a regression analysis is 0.11 and each independent variable is highly correlated to the dependent variable,what does this indicate?

Twenty-one executives in a large corporation were randomly selected for a study to determine the effect of several factors on annual salary (expressed in $000's).The factors selected were age,seniority,years of college,number of company divisions they had been exposed to and the level of their responsibility.A regression analysis was performed using a popular spreadsheet program with the following regression output: Write out the multiple regression equation._______________________

For a unit change in the first independent variable with other things being held constant,what change can be expected in the dependent variable in the multiple regression equation ?

If the null hypothesis,H_o: $\beta$ ₁ = 0 ,is rejected,what effect does the independent variable,X₁,have when predicting the dependent variable? ______

A real estate agent developed a model to relate a house's selling price (Y)to the area of floor space (X)and the area of floor space squared .The multiple regression equation for this model is: where: = selling price (times $1000) X = square feet of floor space (times 100) What is the selling price of a house with 1000 square feet? ______

In a multiple regression analysis ANOVA table,what determines the number of degrees of freedom associated with the regression sum of squares? ____________________.