Question 1

In reference to the equation   , the value -0.75 is the intercept.

Accepted Answer

A) True 
 B)False

Question 2

In a multiple linear regression model,   ,   is the intercept, while   are the partial slopes, or partial regression coefficients.

Accepted Answer

A) True 
 B)False

Question 3

A regression model of the form   is called a third-order polynomial model.

Accepted Answer

A) True 
 B)False

Question 4

Given MSR = 345 and MSE = 431.25, what is the value of the F statistic?

Accepted Answer

A)  1.25 
B)  0.994 
C)  0.894 
D)  0.800 
A)  1.25 
B)  0.994 
C)  0.894 
D)  0.800

Question 5

Multicollinearity is a situation in which two or more of the independent variables are highly correlated with each other.

Accepted Answer

A) True 
 B)False

Question 6

Life Expectancy Narrative
An actuary wanted to develop a model to predict how long individuals will live. After consulting a number of physicians, she collected the age at death (y), the average number of hours of exercise per week (   ), the cholesterol level (   ), and the number of points that the individual's blood pressure exceeded the recommended value (   ). A random sample of 40 individuals was selected. The computer output of the multiple regression model is shown below.
The regression equation is       S = 9.47 R-Sq = 22.5%
Analysis of Variance  
-Refer to Life Expectancy Narrative. Is there enough evidence at the 10% significance level to infer that the model is useful in predicting length of life?

Accepted Answer

@#IMG-DLM& @#IMG-DLM& At least one @#IMG-DLM& is not equal to 0.
Rejec

Question 7

Which of the following correctly describes a multiple-regression ANOVA test?

Accepted Answer

A)  It is a test of the significance of individual coefficients, rather than of the overall significance of the regression model. 
B)  It amounts to testing the hypothesis that none of the true regression coefficients is 0 and that, therefore, all the independent predictors help explain the variation of the dependent variable. 
C)  It is a test of the overall significance of a regression, rather than a test of the significance of individual coefficients. 
D)  Both A and B 
A)  It is a test of the significance of individual coefficients, rather than of the overall significance of the regression model. 
B)  It amounts to testing the hypothesis that none of the true regression coefficients is 0 and that, therefore, all the independent predictors help explain the variation of the dependent variable. 
C)  It is a test of the overall significance of a regression, rather than a test of the significance of individual coefficients. 
D)  Both A and B

Question 8

What is the range in values of the coefficient of multiple determination?

Accepted Answer

A)  from 1.0 to 
B)  from 0.0 to 1.0 
C)  from 1.0 to k, where k is the number of independent variables in the model 
D)  from 1.0 to n, where n is the number of observations in the dependent variable 
A)  from 1.0 to 
B)  from 0.0 to 1.0 
C)  from 1.0 to k, where k is the number of independent variables in the model 
D)  from 1.0 to n, where n is the number of observations in the dependent variable

Question 9

A coefficient of multiple correlation, denoted by R, equals the proportion of the total variation in the values of the dependent variable, Y, that is explained by the estimated multiple regression of Y on   and possibly additional independent variables (   and so on).

Accepted Answer

A) True 
 B)False

Question 10

In multiple regression models, which of the following may be assumed in with respect to the values of the error variable   ?

Accepted Answer

A)  They are autocorrelated. 
B)  They are dependent on each other. 
C)  They are independent of each other. 
D)  They are always positive. 
A)  They are autocorrelated. 
B)  They are dependent on each other. 
C)  They are independent of each other. 
D)  They are always positive.

Question 11

A multiple regression analysis involving 3 independent variables and 25 data points results in a value of 0.769 for the unadjusted multiple coefficient of determination. What is the adjusted multiple coefficient of determination?

Accepted Answer

A)  0.385 
B)  0.591 
C)  0.736 
D)  0.877 
A)  0.385 
B)  0.591 
C)  0.736 
D)  0.877

Question 12

In a multiple regression analysis involving six independent variables, the sum of squares are calculated as: Total SS = 900, SSR = 600, and SSE = 300. In this case, the value of the F-test statistic is 150.

Accepted Answer

A) True 
 B)False

Question 13

Demographic Variables and TV Narrative
A statistician wanted to determine if the demographic variables of age, education, and income influence the number of hours of television watched per week. A random sample of 25 adults was selected to estimate the multiple regression model:   , where y is the number of hours of television watched last week,   is the age (in years),   is the number of years of education, and   is income (in $1000s). The computer output is shown below.
The regression equation is       S = 4.51 R-Sq = 34.8%
Analysis of Variance  
-Refer to Demographic Variables and TV Narrative. Interpret the coefficient   .

Accepted Answer

@#IMG-DLM& = -0.29. This tells us that, for each a

Question 14

A multiple regression equation includes five independent variables, and the coefficient of determination is 0.81. The percentage of the variation in   that is explained by the regression equation is 90%.

Accepted Answer

A) True 
 B)False

Question 15

Demographic Variables and TV Narrative
A statistician wanted to determine if the demographic variables of age, education, and income influence the number of hours of television watched per week. A random sample of 25 adults was selected to estimate the multiple regression model:   , where y is the number of hours of television watched last week,   is the age (in years),   is the number of years of education, and   is income (in $1000s). The computer output is shown below.
The regression equation is       S = 4.51 R-Sq = 34.8%
Analysis of Variance  
-Refer to Demographic Variables and TV Narrative. Interpret the coefficient   .

Accepted Answer

@#IMG-DLM& = 0.41. This tells us that, for each ad

Question 16

Consider a multiple regression model with three independent variables. If the y-intercept is negative, then at least two of the partial regression slope coefficients will also be negative.

Accepted Answer

A) True 
 B)False

Question 17

It is appropriate to compute a correlation coefficient for the relationship between a dummy variable and a dependent variable.

Accepted Answer

A) True 
 B)False

Question 18

A regression model of the form   is called a quadratic model or a second-order polynomial model.

Accepted Answer

A) True 
 B)False

Question 19

Rocket Experiments Narrative
An engineer was investigating the relationship between the thrust of an experimental rocket (y), the percent composition of a secret chemical in the fuel (xS1U1B11S1U1B0), and the internal temperature of a chamber of the rocket (xS1U1B12S1U1B0). The engineer starts by fitting a quadratic model, but he believes that the full quadratic model is too complex and can be reduced by including only the linear terms and the interaction term.
-Refer to Rocket Experiments Narrative. Write the two models the engineer is considering.

Accepted Answer

Complete m

Question 20

In a multiple linear regression model,   ,   are independent predictor variables that are measured without error.

Accepted Answer

A) True 
 B)False

In reference to the equation , the value -0.75 is the intercept.

In a multiple linear regression model, , is the intercept, while are the partial slopes, or partial regression coefficients.

A regression model of the form is called a third-order polynomial model.

Given MSR = 345 and MSE = 431.25, what is the value of the F statistic?

Multicollinearity is a situation in which two or more of the independent variables are highly correlated with each other.

Which of the following correctly describes a multiple-regression ANOVA test?

What is the range in values of the coefficient of multiple determination?

A coefficient of multiple correlation, denoted by R, equals the proportion of the total variation in the values of the dependent variable, Y, that is explained by the estimated multiple regression of Y on and possibly additional independent variables ( and so on).

In multiple regression models, which of the following may be assumed in with respect to the values of the error variable ?

A multiple regression analysis involving 3 independent variables and 25 data points results in a value of 0.769 for the unadjusted multiple coefficient of determination. What is the adjusted multiple coefficient of determination?

In a multiple regression analysis involving six independent variables, the sum of squares are calculated as: Total SS = 900, SSR = 600, and SSE = 300. In this case, the value of the F-test statistic is 150.

A multiple regression equation includes five independent variables, and the coefficient of determination is 0.81. The percentage of the variation in that is explained by the regression equation is 90%.

Consider a multiple regression model with three independent variables. If the y-intercept is negative, then at least two of the partial regression slope coefficients will also be negative.

It is appropriate to compute a correlation coefficient for the relationship between a dummy variable and a dependent variable.

A regression model of the form is called a quadratic model or a second-order polynomial model.

In a multiple linear regression model, , are independent predictor variables that are measured without error.

Describing Data With Graphs

Describing Data With Numerical Measures

Describing Bivariate Data

A: probability and Probability Distributions

B: probability and Probability Distributions

Several Useful Discrete Distributions

The Normal Probability Distribution

Sampling Distributions

Large-Sample Estimation

A: large-Sample Tests of Hypotheses

B: large-Sample Tests of Hypotheses

A: Inference From Small Samples

B: Inference From Small Samples

A: The Analysis of Variance

B: The Analysis of Variance

A: linear Regression and Correlation

B: linear Regression and Correlation

Analysis of Categorical Data

A:nonparametric Statistics

B:nonparametric Statistics

Filters

Exam 13: Multiple Regression Analysis

In reference to the equation , the value -0.75 is the intercept.

In a multiple linear regression model, , is the intercept, while are the partial slopes, or partial regression coefficients.

A regression model of the form is called a third-order polynomial model.

Given MSR = 345 and MSE = 431.25, what is the value of the F statistic?

Multicollinearity is a situation in which two or more of the independent variables are highly correlated with each other.

Which of the following correctly describes a multiple-regression ANOVA test?

What is the range in values of the coefficient of multiple determination?

A coefficient of multiple correlation, denoted by R, equals the proportion of the total variation in the values of the dependent variable, Y, that is explained by the estimated multiple regression of Y on and possibly additional independent variables ( and so on).

In multiple regression models, which of the following may be assumed in with respect to the values of the error variable ?

A multiple regression analysis involving 3 independent variables and 25 data points results in a value of 0.769 for the unadjusted multiple coefficient of determination. What is the adjusted multiple coefficient of determination?

In a multiple regression analysis involving six independent variables, the sum of squares are calculated as: Total SS = 900, SSR = 600, and SSE = 300. In this case, the value of the F-test statistic is 150.

A multiple regression equation includes five independent variables, and the coefficient of determination is 0.81. The percentage of the variation in that is explained by the regression equation is 90%.

Consider a multiple regression model with three independent variables. If the y-intercept is negative, then at least two of the partial regression slope coefficients will also be negative.

It is appropriate to compute a correlation coefficient for the relationship between a dummy variable and a dependent variable.

A regression model of the form is called a quadratic model or a second-order polynomial model.

In a multiple linear regression model, , are independent predictor variables that are measured without error.

Describing Data With Graphs

Describing Data With Numerical Measures

Describing Bivariate Data

A: probability and Probability Distributions

B: probability and Probability Distributions

Several Useful Discrete Distributions

The Normal Probability Distribution

Sampling Distributions

Large-Sample Estimation

A: large-Sample Tests of Hypotheses

B: large-Sample Tests of Hypotheses

A: Inference From Small Samples

B: Inference From Small Samples

A: The Analysis of Variance

B: The Analysis of Variance

A: linear Regression and Correlation

B: linear Regression and Correlation

Analysis of Categorical Data

A:nonparametric Statistics

B:nonparametric Statistics

Filters