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How much does tire production increase for every thousand cars produced two years ago?


A) 670
B) 67
C) 0.67
D) 6.7

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A multiple regression analysis showed the following results of the individual independent variables. A multiple regression analysis showed the following results of the individual independent variables. In stepwise regression, which independent variable would most likely be added first? A) X1 B) X2 C) X3 D) X4 In stepwise regression, which independent variable would most likely be added first?


A) X1
B) X2
C) X3
D) X4

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Angela Chou has been asked to investigate the determinants of poverty in Ontario communities. She collected data on 60 communities from Statistics Canada. She selected the percentage of poor Persons living under the poverty line [Poor (%) ], measured by Low Income Cut-Off, designed by Statistics Canada as a measure of poverty for a community, as the dependent variable. The Independent variables selected are percent of single families in each community, the Unemployment rate in each community, percent of population in the community holding a bachelor's Degree as their highest level of education attained, and percent of population holding a High School Diploma as their highest level of education attained. Using the outputs below for this data Set, determine whether Angela should use the model with the high school data included, or the Data without the high school data, and why. Angela Chou has been asked to investigate the determinants of poverty in Ontario communities. She collected data on 60 communities from Statistics Canada. She selected the percentage of poor Persons living under the poverty line [Poor (%) ], measured by Low Income Cut-Off, designed by Statistics Canada as a measure of poverty for a community, as the dependent variable. The Independent variables selected are percent of single families in each community, the Unemployment rate in each community, percent of population in the community holding a bachelor's Degree as their highest level of education attained, and percent of population holding a High School Diploma as their highest level of education attained. Using the outputs below for this data Set, determine whether Angela should use the model with the high school data included, or the Data without the high school data, and why. A) It doesn't matter which she uses, the results are virtually the same in either case. B) Angela should use the data that includes the high school information, because more information is always better than less information. C) Angela should use the data that includes the high school information, because the calculated F value is lower. D) Angela should include the high school data because the P-value is 0.977, close to 1. E) Angela should exclude the high school data because the adjusted R-squared value is a little higher than in the data that includes the high school information. Angela Chou has been asked to investigate the determinants of poverty in Ontario communities. She collected data on 60 communities from Statistics Canada. She selected the percentage of poor Persons living under the poverty line [Poor (%) ], measured by Low Income Cut-Off, designed by Statistics Canada as a measure of poverty for a community, as the dependent variable. The Independent variables selected are percent of single families in each community, the Unemployment rate in each community, percent of population in the community holding a bachelor's Degree as their highest level of education attained, and percent of population holding a High School Diploma as their highest level of education attained. Using the outputs below for this data Set, determine whether Angela should use the model with the high school data included, or the Data without the high school data, and why. A) It doesn't matter which she uses, the results are virtually the same in either case. B) Angela should use the data that includes the high school information, because more information is always better than less information. C) Angela should use the data that includes the high school information, because the calculated F value is lower. D) Angela should include the high school data because the P-value is 0.977, close to 1. E) Angela should exclude the high school data because the adjusted R-squared value is a little higher than in the data that includes the high school information.


A) It doesn't matter which she uses, the results are virtually the same in either case.
B) Angela should use the data that includes the high school information, because more information is always better than less information.
C) Angela should use the data that includes the high school information, because the calculated F value is lower.
D) Angela should include the high school data because the P-value is 0.977, close to 1.
E) Angela should exclude the high school data because the adjusted R-squared value is a little higher than in the data that includes the high school information.

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It has been hypothesized that overall academic success for freshmen at college as measured by Grade point average (GPA) is a function of IQ scores (X1) , hours spent studying each week (X2) , and One's high school average (X3) . Suppose the regression equation is: Y' = -6.9 + 0.055X1 + 0.107X2 + 0.0083X3. The multiple standard error is 6.313 and R2 = 0.826.For which independent variable does a unit Change have the greatest effect on the GPA?


A) IQ scores (X1)
B) hours spent studying each week (X2)
C) high school average (X3)

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i. The values of b1, b2 and b3 in a multiple regression equation are called the net regression Coefficients. They indicate the change in the predicted value for a unit change in one X when the Other X variables are held constant. ii. A multiple regression equation defines the relationship between the dependent variable and the Independent variables in the form of an equation. iii. If an inverse relationship exists between the dependent variable and independent variables, the Regression coefficients for the independent variables are positive.


A) (i) , (ii) , and (iii) are all correct statements.
B) (i) and (ii) are correct statements but not (iii) .
C) (i) and (iii) are correct statements but not (ii) .
D) (ii) and (iii) are correct statements but not (i) .
E) (i) , (ii) , and (iii) are all false statements.

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What is the equation for our model?


A) Y'= -50000 + 5.00X1 + 0.25X2 + 0.67X3 + 2.12X4 + 3.44X5
B) Y'= 0.25X2 + 0.67X3 + 2.12X4 - 3.44X5
C) Y'= 5.00X1 - 0.25X2 - 0.67X3 + 2.12X4 + 3.44X5
D) Y'= 10.4X1 + 0.6X2 + 1.4.X3 + 2.7X4 + 6.5X5

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i. A variable whose possible outcomes are coded as a "1" or a "0" is called a dummy variable. ii. A dummy variable is added to the regression equation to control for error. iii. If the null hypothesis β4 = 0 is not rejected, then the independent variable X4 has no effect in Predicting the dependent variable.


A) (i) , (ii) , and (iii) are all correct statements.
B) (i) and (ii) are correct statements but not (iii) .
C) (i) and (iii) are correct statements but not (ii) .
D) (ii) and (iii) are correct statements but not (i) .
E) (i) , (ii) , and (iii) are all false statements.

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i. Violating the need for successive observations of the dependent variable to be uncorrelated is Called autocorrelation. ii. If an inverse relationship exists between the dependent variable and independent variables, the Regression coefficients for the independent variables are negative. iii. Given a multiple linear equation Y' = 5.1 + 2.2X1 - 3.5X2, assuming other things are held constant, An increase in one unit of the second independent variable will cause a -3.5 unit change in Y.


A) (i) , (ii) , and (iii) are all correct statements.
B) (i) and (ii) are correct statements but not (iii) .
C) (i) and (iii) are correct statements but not (ii) .
D) (ii) and (iii) are correct statements but not (i) .
E) (i) , (ii) , and (iii) are all false statements.

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A manager at a local bank analyzed the relationship between monthly salary and three independent Variables: length of service (measured in months) , gender (0 = female, 1 = male) and job type (0 = Clerical, 1 = technical) . The following ANOVA summarizes the regression results: A manager at a local bank analyzed the relationship between monthly salary and three independent Variables: length of service (measured in months) , gender (0 = female, 1 = male) and job type (0 = Clerical, 1 = technical) . The following ANOVA summarizes the regression results: Based on the ANOVA, the multiple coefficient of determination is A) 5.957%. B) 59.3%. C) 40.7%. D) cannot be computed. Based on the ANOVA, the multiple coefficient of determination is


A) 5.957%.
B) 59.3%.
C) 40.7%.
D) cannot be computed.

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The best example of a null hypothesis for testing an individual regression coefficient is:


A) H0: β1 = β2 = β3 = β4.
B) H0: μ1 = μ2 = μ3 = μ4.
C) H0: β1 = 0.
D) if F is greater than 20.00 then reject.

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Multiple regression analysis is applied when analyzing the relationship between


A) an independent variable and several dependent variables.
B) a dependent variable and several independent variables.
C) several dependent variables and several independent variables.
D) several regression equations and a single sample.

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Determine the multiple regression equation. _______________________


A) Y' = 23.004 - 0.031X1 + 0.381X2 + 1.452X3 - 0.089X4 + 3.554X5
B) Y' = -23.004 - 0.031X1 + 0.381X2 + 1.45X3 - 0.089X4 + 3.554X5
C) Y' = 23.004 - 0.031X1 + 0.381X2 + 1.452X3 + 0.089X4 - 3.554X5
D) Y' = 23.004 - 0.031X1 - 0.381X2 - 1.452X3 - 0.089X4 + 3.554X5
E) Y' = -23.004 + 0.031X1 - 0.381X2 - 1.45X3 + 0.089X4 - 3.554X5

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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 Y' = 5.2 + 6) 3X1 - 7.1X2?


A) -7.1
B) +6.3
C) +5.2
D) +4.4

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The information below is from the multiple regression analysis computer output for 28 teams in Major League Baseball. The model is designed to predict wins using attendance, payroll, batting Average, home runs, stolen bases, errors, and team ERA. The information below is from the multiple regression analysis computer output for 28 teams in Major League Baseball. The model is designed to predict wins using attendance, payroll, batting Average, home runs, stolen bases, errors, and team ERA. Predict the number of wins for a team with: BATAVG = 0.260 HOMERUNS = 150 ERA = 3 STOLENBASE = 100 ERROR = 100 PAYROLL = 25(million) ATTENDANCE = 3(million) A) 77 B) 102 C) 187 D) 210 E) 186 Multiple Choice Difficulty: Hard Learning Predict the number of wins for a team with: BATAVG = 0.260 HOMERUNS = 150 ERA = 3 STOLENBASE = 100 ERROR = 100 PAYROLL = 25(million) ATTENDANCE = 3(million)


A) 77
B) 102
C) 187
D) 210
E) 186 Multiple Choice Difficulty: Hard Learning

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How much does tire production change for every thousand cars produced three years ago?


A) 2120
B) 212
C) 21.2
D) 2.12

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A sample of General Mills employees was studied to determine their degree of satisfaction with Their present life. A special index, called the index of satisfaction, was used to measure satisfaction. Six factors were studied: age at the time of first marriage (X1) , annual income (X2) , number of Children living (X3) , value of all assets (X4) , status of health in the form of an index (X5) , and the Average number of social activities per week (X6) . Suppose the multiple regression equation is: Y' = 16.24 + 0.017X1 + 0.00028X2 + 42X3 + 0.0012X4 + 0.19X5 + 26.8X6. What is the estimated index of satisfaction for a person who first married at 25, has an annual Income of $26,500, has two children, has assets of $156,000, has in index of health status of 141, And has 2.5 social activities per week?


A) 389.1
B) 421.6
C) 366.0
D) 601.6
E) 769.8

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The following graph is used to evaluate an assumption of a multiple regression analysis. What is the Assumption? The following graph is used to evaluate an assumption of a multiple regression analysis. What is the Assumption? A) Normal distribution of residuals B) Linearity C) Homoscedasticity D) Scatter diagram


A) Normal distribution of residuals
B) Linearity
C) Homoscedasticity
D) Scatter diagram

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Which of the following has the most influence on salary--20 years of seniority, 5 years of college or Attaining 55 years of age?


A) 20 years of seniority
B) 5 years of college
C) attaining 55 years of age
D) seniority, education and age all have equal influence on salary

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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?


A) Multicollinearity between these two independent variables.
B) Negative relationship is not possible.
C) Only one of the two independent variables will explain a high percent of the variation.
D) An effective regression equation.

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It is thought that there are a variety of factors that affect a teacher's salary. Using the following Printout and sample data, determine whether the holding of a PhD degree is a significant variable When tested at the 5% level of significance. It is thought that there are a variety of factors that affect a teacher's salary. Using the following Printout and sample data, determine whether the holding of a PhD degree is a significant variable When tested at the 5% level of significance. A) Since the p-value is less than the level of significance, the null hypothesis is rejected, and so the holding of a PhD should be included in the analysis. B) Since the p-value is less than the level of significance, the null hypothesis is accepted, and so the PhD should not be included in the analysis. C) Since the p-value is more than the level of significance, the null hypothesis is accepted, and so the PhD should not be included in the analysis. D) Since the p-value is more than the level of significance, the null hypothesis is rejected, and so the PhD should be included in the analysis. It is thought that there are a variety of factors that affect a teacher's salary. Using the following Printout and sample data, determine whether the holding of a PhD degree is a significant variable When tested at the 5% level of significance. A) Since the p-value is less than the level of significance, the null hypothesis is rejected, and so the holding of a PhD should be included in the analysis. B) Since the p-value is less than the level of significance, the null hypothesis is accepted, and so the PhD should not be included in the analysis. C) Since the p-value is more than the level of significance, the null hypothesis is accepted, and so the PhD should not be included in the analysis. D) Since the p-value is more than the level of significance, the null hypothesis is rejected, and so the PhD should be included in the analysis.


A) Since the p-value is less than the level of significance, the null hypothesis is rejected, and so the holding of a PhD should be included in the analysis.
B) Since the p-value is less than the level of significance, the null hypothesis is accepted, and so the PhD should not be included in the analysis.
C) Since the p-value is more than the level of significance, the null hypothesis is accepted, and so the PhD should not be included in the analysis.
D) Since the p-value is more than the level of significance, the null hypothesis is rejected, and so the PhD should be included in the analysis.

Correct Answer

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