Question 1

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

Accepted Answer

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. 
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.

Question 2

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.

Accepted Answer

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.

Question 3

Multiple regression analysis is applied when analyzing the relationship between

Accepted Answer

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. 
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.

Question 4

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?

Accepted Answer

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

Question 5

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?

Accepted Answer

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

Question 6

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?

Accepted Answer

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. 
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.

Question 7

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

Accepted Answer

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

Question 8

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

Accepted Answer

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

Question 9

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

Accepted Answer

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

Question 10

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?

Accepted Answer

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

Question 11

Determine the multiple regression equation. _______________________

Accepted Answer

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 
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

Question 12

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.

Accepted Answer

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.

Question 13

What is the equation for our model?

Accepted Answer

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 
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

Question 14

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.

Accepted Answer

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. 
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.

Question 15

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?

Accepted Answer

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

Question 16

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.

Accepted Answer

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. 
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.

Question 17

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.

Accepted Answer

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. 
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.

Question 18

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

Accepted Answer

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 
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

Question 19

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)

Accepted Answer

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

Question 20

The following graph is used to evaluate an assumption of a multiple regression analysis. What is the
Assumption?

Accepted Answer

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

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

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.

Multiple regression analysis is applied when analyzing the relationship between

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?

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

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

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?

Determine the multiple regression equation. _______________________

What is the equation for our model?

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?

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

The following graph is used to evaluate an assumption of a multiple regression analysis. What is the Assumption?

What Is Statistics

Describing Data: Frequencydistributions and Graphic Presentation

Describing Data: Numerical Measures

Describing Data: Displaying and Exploring Pata

A Sulvey of Probability Concepts

Discrete Probability Distributions

Continuous Probabilitydistributions

Sampling Methods and the Central Umit Theorem

Estimation and Confidence Intervals

One-Sample Tests of Hypothesis

Two Sample Tests of Hypothesis

Analysis of Variance

Multiple Regression and Correlation Analysis

Chi-Square Applications

Decision Making and Payoff Tables in Investment Scenarios

Filters

Exam 13: Linear Regression and Correlation

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

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.

Multiple regression analysis is applied when analyzing the relationship between

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?

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

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

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?

Determine the multiple regression equation. _______________________

What is the equation for our model?

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?

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

The following graph is used to evaluate an assumption of a multiple regression analysis. What is the Assumption?

What Is Statistics

Describing Data: Frequencydistributions and Graphic Presentation

Describing Data: Numerical Measures

Describing Data: Displaying and Exploring Pata

A Sulvey of Probability Concepts

Discrete Probability Distributions

Continuous Probabilitydistributions

Sampling Methods and the Central Umit Theorem

Estimation and Confidence Intervals

One-Sample Tests of Hypothesis

Two Sample Tests of Hypothesis

Analysis of Variance

Multiple Regression and Correlation Analysis

Chi-Square Applications

Decision Making and Payoff Tables in Investment Scenarios

Filters