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If the Durbin-Watson statistic d has values smaller than 2,this indicates


A) a positive first-order autocorrelation
B) a negative first-order autocorrelation
C) no first-order autocorrelation at all
D) None of these choices.

E) A) and C)
F) C) and D)

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The coefficient of determination ____________________ for degrees of freedom takes into account the sample size and the number of independent variables when assessing model fit.

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A multiple regression model is assessed to be poor if the error sum of squares SSE and the standard error of estimate sε are both large,the coefficient of determination R2 is close to 0,and the value of the test statistic F is large.

A) True
B) False

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Multicollinearity affects the t-tests of the individual coefficients as well as the F-test in the analysis of variance for regression because the F-test combines the t-tests into a single test.

A) True
B) False

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For the following multiple regression model: For the following multiple regression model:   ,a unit increase in x<sub>1</sub>,holding x<sub>2</sub> and x<sub>3</sub> constant,results in: A) a decrease of 3 units on average in the value of y. B) an increase of 8 units in the value of y. C) an increase of 3 units on average in the value of y. D) None of these choices. ,a unit increase in x1,holding x2 and x3 constant,results in:


A) a decrease of 3 units on average in the value of y.
B) an increase of 8 units in the value of y.
C) an increase of 3 units on average in the value of y.
D) None of these choices.

E) All of the above
F) A) and C)

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Real Estate Builder A real estate builder wishes to determine how house size is influenced by family income,family size,and education of the head of household.House size is measured in hundreds of square feet,income is measured in thousands of dollars,and education is measured in years.A partial computer output is shown below. SUMMARY OUTPUT Regression Statistics Multiple R 0.865 R Square 0.748 Adjusted R Square 0.726 Standard Error 5.195 Observations 50 ANOVA  Real Estate Builder  A real estate builder wishes to determine how house size is influenced by family income,family size,and education of the head of household.House size is measured in hundreds of square feet,income is measured in thousands of dollars,and education is measured in years.A partial computer output is shown below. SUMMARY OUTPUT Regression Statistics Multiple R 0.865 R Square 0.748 Adjusted R Square 0.726 Standard Error 5.195 Observations 50 ANOVA     ​ ​ -{Real Estate Builder Narrative} Which of the following values for the level of significance is the smallest for which the regression model as a whole is significant: α = .00005,.001,.01,and .05?  Real Estate Builder  A real estate builder wishes to determine how house size is influenced by family income,family size,and education of the head of household.House size is measured in hundreds of square feet,income is measured in thousands of dollars,and education is measured in years.A partial computer output is shown below. SUMMARY OUTPUT Regression Statistics Multiple R 0.865 R Square 0.748 Adjusted R Square 0.726 Standard Error 5.195 Observations 50 ANOVA     ​ ​ -{Real Estate Builder Narrative} Which of the following values for the level of significance is the smallest for which the regression model as a whole is significant: α = .00005,.001,.01,and .05? ​ ​ -{Real Estate Builder Narrative} Which of the following values for the level of significance is the smallest for which the regression model as a whole is significant: α = .00005,.001,.01,and .05?

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Real Estate Builder A real estate builder wishes to determine how house size is influenced by family income,family size,and education of the head of household.House size is measured in hundreds of square feet,income is measured in thousands of dollars,and education is measured in years.A partial computer output is shown below. SUMMARY OUTPUT Regression Statistics Multiple R 0.865 R Square 0.748 Adjusted R Square 0.726 Standard Error 5.195 Observations 50 ANOVA  Real Estate Builder  A real estate builder wishes to determine how house size is influenced by family income,family size,and education of the head of household.House size is measured in hundreds of square feet,income is measured in thousands of dollars,and education is measured in years.A partial computer output is shown below. SUMMARY OUTPUT Regression Statistics Multiple R 0.865 R Square 0.748 Adjusted R Square 0.726 Standard Error 5.195 Observations 50 ANOVA     ​ ​ -{Real Estate Builder Narrative} Suppose the builder wants to test whether the coefficient on income is significantly different from 0.What is the value of the relevant t-statistic?  Real Estate Builder  A real estate builder wishes to determine how house size is influenced by family income,family size,and education of the head of household.House size is measured in hundreds of square feet,income is measured in thousands of dollars,and education is measured in years.A partial computer output is shown below. SUMMARY OUTPUT Regression Statistics Multiple R 0.865 R Square 0.748 Adjusted R Square 0.726 Standard Error 5.195 Observations 50 ANOVA     ​ ​ -{Real Estate Builder Narrative} Suppose the builder wants to test whether the coefficient on income is significantly different from 0.What is the value of the relevant t-statistic? ​ ​ -{Real Estate Builder Narrative} Suppose the builder wants to test whether the coefficient on income is significantly different from 0.What is the value of the relevant t-statistic?

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When an explanatory variable is dropped from a multiple regression model,the adjusted coefficient of determination can increase.

A) True
B) False

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Because of multicollinearity,the t-tests of the individual coefficients may indicate that some independent variables are not linearly related to the dependent variable,when in fact they are.

A) True
B) False

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If the value of the Durbin-Watson statistic d is small (d < 2),this indicates a(n)____________________ (positive/negative)first-order autocorrelation exists.

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In a multiple regression analysis involving 6 independent variables,the total variation in y is 900 and SSR = 600.What is the value of SSE?


A) 300
B) 1.50
C) 0.67
D) None of these choices.

E) None of the above
F) A) and C)

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When an explanatory variable is dropped from a multiple regression model,the coefficient of determination can increase.

A) True
B) False

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How do you go about checking for multicollinearity?

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A practical way to identify multicolline...

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Test the hypotheses H0: no first-order autocorrelation vs.H1: first-order autocorrelation,given that: Durbin-Watson Statistic d = 1.89,n = 28,k = 3,and α = 0.01.

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dL = 0.97 and dU = 1.41 The decision is ma...

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When the independent variables are correlated with one another in a multiple regression analysis,this condition is called:


A) heteroscedasticity.
B) homoscedasticity.
C) multicollinearity.
D) None of these choices.

E) A) and D)
F) None of the above

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Three predictor variables are being considered for use in a linear regression model.Given the correlation matrix below,does it appear that multicollinearity could be a problem? Three predictor variables are being considered for use in a linear regression model.Given the correlation matrix below,does it appear that multicollinearity could be a problem?

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It appears that multicollinear...

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The Durbin-Watson statistic,d,is defined as The Durbin-Watson statistic,d,is defined as   ,where e<sub>i</sub> is the residual at time period i. ,where ei is the residual at time period i.

A) True
B) False

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A multiple regression model involves 5 independent variables and a sample of 10 data points.If we want to test the validity of the model at the 5% significance level,the critical value is:


A) 6.26
B) 3.33
C) 9.36
D) 4.24

E) B) and C)
F) B) and D)

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Given that the Durbin-Watson test is conducted to test for positive first-order autocorrelation with α = .05,n = 20,and there are two independent variables in the model,the critical values for the test are dL = __________ and dU = __________,respectively.

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A multiple regression model involves 10 independent variables and 30 observations.If we want to test at the 5% significance level whether one of the coefficients is = 0 (vs.≠ 0) the critical value will be:


A) 2.228
B) 2.093
C) 1.729
D) 1.697

E) A) and D)
F) A) and C)

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