Question 1

If SSR = 3600,SSE = 1200,and SST = 4800,then R2 is

Accepted Answer

A) 0.5000 
B) 0.7500 
C) 0.3333 
D) 0.2500 
A) 0.5000 
B) 0.7500 
C) 0.3333 
D) 0.2500

Question 2

Statisticians who work with cross-sectional data generally do not anticipate autocorrelation.

Accepted Answer

A) True 
 B)False

Question 3

Analyze the regression results below (n = 33 cars in 1993)using the concepts you have learned about multiple regression.Circle things of interest and write comments in the margin.Make a prediction for CityMPG for a car with EngSize = 2.5,ManTran = 1,Length = 184,Wheelbase = 104,Weight = 3000,and Domestic = 0 (show your work).The variables are CityMPG = city MPG (miles per gallon by EPA rating);EngSize = engine size (liters);ManTran = 1 if manual transmission available,0 otherwise;Length = vehicle length (inches);Wheelbase = vehicle wheelbase (inches);Weight = vehicle weight (pounds);Domestic = 1 if U.S.manufacturer,0 otherwise.

Accepted Answer

The regression is significant overall (F

Question 4

A fitted multiple regression equation is Y = 28 + 5X1 - 4X2 + 7X3 + 2X4.When X1 increases 2 units and X2 increases 2 units as well,while X3 and X4 remain unchanged,what change would you expect in your estimate of Y?

Accepted Answer

A) Increase by 2 
B) Decrease by 4 
C) Increase by 4 
D) No change in Y 
A) Increase by 2 
B) Decrease by 4 
C) Increase by 4 
D) No change in Y

Question 5

An observation with extreme values in one or more independent variables (predictors)

Accepted Answer

A) has reduced influence on the estimated coefficients. 
B) has increased influence on the estimated coefficients. 
C) causes an overstated estimate of the standard error. 
D) leads to high correlations between the X values. 
A) has reduced influence on the estimated coefficients. 
B) has increased influence on the estimated coefficients. 
C) causes an overstated estimate of the standard error. 
D) leads to high correlations between the X values.

Question 6

A realtor is trying to predict the selling price of houses in Greenville (in thousands of dollars)as a function of Size (measured in thousands of square feet)and whether or not there is a fireplace (FP is 0 if there is no fireplace,1 if there is a fireplace).Part of the regression output is provided below,based on a sample of 20 homes.Some of the information has been omitted.   Which statement is supported by the regression output?

Accepted Answer

A) At α = .05,FP is not a significant predictor in a two-tailed test. 
B) A fireplace adds around $6,476 to the selling price of the average house. 
C) A large house with no fireplace will sell for more than a small house with a fireplace. 
D) FP is a more significant predictor than Size. 
A) At α = .05,FP is not a significant predictor in a two-tailed test. 
B) A fireplace adds around $6,476 to the selling price of the average house. 
C) A large house with no fireplace will sell for more than a small house with a fireplace. 
D) FP is a more significant predictor than Size.

Question 7

The regression equation Salary = 35,000 + 3500 YearsExperience + 1200 YearsCollege describes employee salaries at Streeling Research Labs.The standard error is 2500.Doris has 20 years' experience and 4 years of college.Her salary is $113,000.What is Doris's standardized residual?

Accepted Answer

A) +1.28 
B) −0.24 
C) −1.28 
D) +3.20 
A) +1.28 
B) −0.24 
C) −1.28 
D) +3.20

Question 8

Using state data (n = 50)for the year 2000,a statistics student calculated a matrix of correlation coefficients for selected variables describing state averages on the two main scholastic aptitude tests (ACT and SAT).(a)In the spaces provided,write the two-tailed critical values of the correlation coefficient for α = .05 and α = .01 respectively.Show how you derived these critical values.(b)Mark with * all correlations that are significant at α = .05,and mark with ** those that are significant at α = .01.(c)Why might you expect a negative correlation between ACT% and SAT%? (d)Why might you expect a positive correlation between SATQ and SATV? Explain your reasoning.(e)Why is the matrix empty above the diagonal?

Accepted Answer

(a)As explained in Chapter 12,for d.f.=

Question 9

Autocorrelation of the residuals may affect the reliability of the t-values for the estimated coefficients of the predictors X1,X2,... ,Xk.

Accepted Answer

A) True 
 B)False

Question 10

If you rerun a regression,omitting a predictor X5,which would be unlikely?

Accepted Answer

A) The new R2 will decline if X5 was a relevant predictor. 
B) The new standard error will increase if X5 was a relevant predictor. 
C) The remaining estimated β's will change if X5 was collinear with other predictors. 
D) The numerator degrees of freedom for the F test will increase. 
A) The new R2 will decline if X5 was a relevant predictor. 
B) The new standard error will increase if X5 was a relevant predictor. 
C) The remaining estimated β's will change if X5 was collinear with other predictors. 
D) The numerator degrees of freedom for the F test will increase.

Question 11

Refer to this ANOVA table from a regression:   Which statement is not accurate?

Accepted Answer

A) The F-test is significant at α = .05. 
B) There were 50 observations. 
C) There were 5 predictors. 
D) There would be 50 residuals. 
A) The F-test is significant at α = .05. 
B) There were 50 observations. 
C) There were 5 predictors. 
D) There would be 50 residuals.

Question 12

In a multiple regression with five predictors in a sample of 56 U.S.cities,we would use F5,50 in a test of overall significance.

Accepted Answer

A) True 
 B)False

Question 13

Which is not a standard criterion for assessing a regression model?

Accepted Answer

A) Logic of causation 
B) Overall fit 
C) Degree of collinearity 
D) Binary predictors 
A) Logic of causation 
B) Overall fit 
C) Degree of collinearity 
D) Binary predictors

Question 14

Multicollinearity can be detected from t tests of the predictor variables.

Accepted Answer

A) True 
 B)False

Question 15

In a multiple regression with 3 predictors in a sample of 25 U.S.cities,we would use F3,21 in a test of overall significance.

Accepted Answer

A) True 
 B)False

Question 16

In a regression with n = 100 observations and k = 5 predictors,the criterion for high leverage is

Accepted Answer

A) hi > .06 
B) hi > .12 
C) hi > .18 
D) hi > .24 
A) hi > .06 
B) hi > .12 
C) hi > .18 
D) hi > .24

Question 17

Heteroscedasticity of residuals in regression suggests that there is

Accepted Answer

A) nonconstant variation in the errors. 
B) multicollinearity among the predictors. 
C) nonnormality in the errors. 
D) lack of independence in successive errors. 
A) nonconstant variation in the errors. 
B) multicollinearity among the predictors. 
C) nonnormality in the errors. 
D) lack of independence in successive errors.

Question 18

Which multiple regression equation contains an interaction term?

Accepted Answer

A) y = −92 + 6x12 −12x22 
B) y = 47 −18x1 −3x12 + 6x2 + 36x22 
C) y = 88 + 11x1 + 7x1x2 + 5x2 
A) y = −92 + 6x12 −12x22 
B) y = 47 −18x1 −3x12 + 6x2 + 36x22 
C) y = 88 + 11x1 + 7x1x2 + 5x2

Question 19

A disadvantage of Excel's regression is that it does not give as much accuracy in the estimated regression coefficients as a package like Minitab.

Accepted Answer

A) True 
 B)False

Question 20

A test is conducted in 22 cities to see if giving away free transit system maps will increase the number of bus riders.In a regression analysis,the dependent variable Y is the increase in bus riders (in thousands of persons)from the start of the test until its conclusion.The independent variables are X1 = the number (in thousands)of free maps distributed and a binary variable X2 = 1 if the city has free downtown parking,0 otherwise.The estimated regression equation is Y = 1.32 + 0.0345X1 − 1.45X2.In city 3,the observed Y value is 7.3,X1 = 140,and X2 = 0.The residual for city 3 (in thousands)is

Accepted Answer

A) 6.15 
B) 1.15 
C) 4.83 
D) 1.57 
A) 6.15 
B) 1.15 
C) 4.83 
D) 1.57

If SSR = 3600,SSE = 1200,and SST = 4800,then R2 is

Statisticians who work with cross-sectional data generally do not anticipate autocorrelation.

A fitted multiple regression equation is Y = 28 + 5X1 - 4X2 + 7X3 + 2X4.When X1 increases 2 units and X2 increases 2 units as well,while X3 and X4 remain unchanged,what change would you expect in your estimate of Y?

An observation with extreme values in one or more independent variables (predictors)

The regression equation Salary = 35,000 + 3500 YearsExperience + 1200 YearsCollege describes employee salaries at Streeling Research Labs.The standard error is 2500.Doris has 20 years' experience and 4 years of college.Her salary is $113,000.What is Doris's standardized residual?

Autocorrelation of the residuals may affect the reliability of the t-values for the estimated coefficients of the predictors X1,X2,... ,Xk.

If you rerun a regression,omitting a predictor X5,which would be unlikely?

Refer to this ANOVA table from a regression: Which statement is not accurate?

In a multiple regression with five predictors in a sample of 56 U.S.cities,we would use F5,50 in a test of overall significance.

Which is not a standard criterion for assessing a regression model?

Multicollinearity can be detected from t tests of the predictor variables.

In a multiple regression with 3 predictors in a sample of 25 U.S.cities,we would use F3,21 in a test of overall significance.

In a regression with n = 100 observations and k = 5 predictors,the criterion for high leverage is

Heteroscedasticity of residuals in regression suggests that there is

Which multiple regression equation contains an interaction term?

A disadvantage of Excel's regression is that it does not give as much accuracy in the estimated regression coefficients as a package like Minitab.

Overview of Statistics

Data Collection

Describing Data Visually

Descriptive Statistics

Probability

Discrete Probability Distributions

Continuous Probability Distributions

Sampling Distributions and Estimation

One-Sample Hypothesis Tests

Two-Sample Hypothesis Tests

Analysis of Variance

Simple Regression

Chi-Square Tests

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Exam 13: Multiple Regression

If SSR = 3600,SSE = 1200,and SST = 4800,then R2 is

Statisticians who work with cross-sectional data generally do not anticipate autocorrelation.

A fitted multiple regression equation is Y = 28 + 5X1 - 4X2 + 7X3 + 2X4.When X1 increases 2 units and X2 increases 2 units as well,while X3 and X4 remain unchanged,what change would you expect in your estimate of Y?

An observation with extreme values in one or more independent variables (predictors)

The regression equation Salary = 35,000 + 3500 YearsExperience + 1200 YearsCollege describes employee salaries at Streeling Research Labs.The standard error is 2500.Doris has 20 years' experience and 4 years of college.Her salary is $113,000.What is Doris's standardized residual?

Autocorrelation of the residuals may affect the reliability of the t-values for the estimated coefficients of the predictors X1,X2,... ,Xk.

If you rerun a regression,omitting a predictor X5,which would be unlikely?

Refer to this ANOVA table from a regression: Which statement is not accurate?

In a multiple regression with five predictors in a sample of 56 U.S.cities,we would use F5,50 in a test of overall significance.

Which is not a standard criterion for assessing a regression model?

Multicollinearity can be detected from t tests of the predictor variables.

In a multiple regression with 3 predictors in a sample of 25 U.S.cities,we would use F3,21 in a test of overall significance.

In a regression with n = 100 observations and k = 5 predictors,the criterion for high leverage is

Heteroscedasticity of residuals in regression suggests that there is

Which multiple regression equation contains an interaction term?

A disadvantage of Excel's regression is that it does not give as much accuracy in the estimated regression coefficients as a package like Minitab.

Overview of Statistics

Data Collection

Describing Data Visually

Descriptive Statistics

Probability

Discrete Probability Distributions

Continuous Probability Distributions

Sampling Distributions and Estimation

One-Sample Hypothesis Tests

Two-Sample Hypothesis Tests

Analysis of Variance

Simple Regression

Chi-Square Tests

Filters