Question 1

What is the value of the denominator in the calculation of the multiple standard error of estimate?

Accepted Answer

A)  15 
B)  21 
C)  6 
D)  5 
A)  15 
B)  21 
C)  6 
D)  5

Question 2

If a multiple regression analysis is based on ten independent variables collected from a sample of
125 observations, what will be the value of the denominator in the calculation of the multiple
Standard error of estimate?

Accepted Answer

A)  125 
B)  10 
C)  114 
D)  115 
A)  125 
B)  10 
C)  114 
D)  115

Question 3

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.
Given the regression equation Poor (%) = -3.81 + 0.798 Single-Families (%) + 0.624 Unemployment
Rate (%) - 0.170 Bachelor's Degree (%) - 0.003 High School (%).
How many dependent variables are there in this regression?

Accepted Answer

A)  1 
B)  2 
C)  3 
D)  4 
E)  5 
A)  1 
B)  2 
C)  3 
D)  4 
E)  5

Question 4

What can we conclude if the net regression coeﬃcients in the population are not signiﬁcantly
Different from zero?

Accepted Answer

A)  Strong relationship exists among the variables. 
B)  No relationship exists between the dependent variable and the independent variables. 
C)  Independent variables are good predictors. 
D)  Good forecasts are possible. 
A)  Strong relationship exists among the variables. 
B)  No relationship exists between the dependent variable and the independent variables. 
C)  Independent variables are good predictors. 
D)  Good forecasts are possible.

Question 5

What happens as the scatter of data values about the regression plane increases?

Accepted Answer

A)  Standard error of estimate increases. 
B)  R2 decreases. 
C)  (1 - R2) decreases. 
D)  Residual sum of squares decreases. 
E)  (1 - R2), residual sum of squares and standard error of estimate all increase, and R2 decreases. 
A)  Standard error of estimate increases. 
B)  R2 decreases. 
C)  (1 - R2) decreases. 
D)  Residual sum of squares decreases. 
E)  (1 - R2), residual sum of squares and standard error of estimate all increase, and R2 decreases.

Question 6

What is the difference in selling prices of a house with 1,600 square feet and one with 1,700 square
Feet?

Accepted Answer

A)  $30 000 
B)  $3000 
C)  $363 000 
D)  $333 000 
A)  $30 000 
B)  $3000 
C)  $363 000 
D)  $333 000

Question 7

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 $100,000, has two children, has assets of $500,000, has in index of health status of 141,
And has 2 social activities per week?

Accepted Answer

A)  777.7 
B)  796.6 
C)  588.6 
D)  601.6 
E)  809.1 
A)  777.7 
B)  796.6 
C)  588.6 
D)  601.6 
E)  809.1

Question 8

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.How will a student's GPA be affected if an
Additional hour is spent studying each weeknight?

Accepted Answer

A)  Increases by 0.535 
B)  Decreases by 0.535 
C)  Increases by 0.107 
D)  Decreases by 0.107 
E)  Increases by 0.0083 
A)  Increases by 0.535 
B)  Decreases by 0.535 
C)  Increases by 0.107 
D)  Decreases by 0.107 
E)  Increases by 0.0083

Question 9

When does multicollinearity occur in a multiple regression analysis?

Accepted Answer

A)  Dependent variables are highly correlated. 
B)  Independent variables are minimally correlated. 
C)  Independent variables are highly correlated. 
D)  Independent variables have no correlation. 
A)  Dependent variables are highly correlated. 
B)  Independent variables are minimally correlated. 
C)  Independent variables are highly correlated. 
D)  Independent variables have no correlation.

Question 10

What does the multiple standard error of estimate measure?

Accepted Answer

A)  Change in Y' for a change in X1. 
B)  Variation of the data points between Y and Y'. 
C)  Variation due to the relationship between the dependent and independent variables. 
D)  Amount of explained variation. 
A)  Change in Y' for a change in X1. 
B)  Variation of the data points between Y and Y'. 
C)  Variation due to the relationship between the dependent and independent variables. 
D)  Amount of explained variation.

Question 11

What is the selling price of a house with 1,500 square feet? ______

Accepted Answer

A)  $305 000 
B)  $125 000 
C)  $300 000 
D)  $1500 000 
A)  $305 000 
B)  $125 000 
C)  $300 000 
D)  $1500 000

Question 12

What is the measurement of explained variation?

Accepted Answer

A)  Coeﬃcient of multiple determination 
B)  Coeﬃcient of multiple nondetermination 
C)  Regression coeﬃcient 
D)  Correlation matrix 
A)  Coeﬃcient of multiple determination 
B)  Coeﬃcient of multiple nondetermination 
C)  Regression coeﬃcient 
D)  Correlation matrix

Question 13

If the coeﬃcient of multiple determination is 0.81, what percent of variation is not explained?

Accepted Answer

A)  19% 
B)  90% 
C)  66% 
D)  81% 
A)  19% 
B)  90% 
C)  66% 
D)  81%

Question 14

Which variable in the model is the least signiﬁcant in predicting tire production?

Accepted Answer

A)  X1 
B)  X2 
C)  X3 
D)  X4 
E)  X5 
A)  X1 
B)  X2 
C)  X3 
D)  X4 
E)  X5

Question 15

What test investigates whether all the independent variables have zero net regression coeﬃcients?

Accepted Answer

A)  Multicollinearity 
B)  Autocorrelation 
C)  Global 
D)  Pearson 
A)  Multicollinearity 
B)  Autocorrelation 
C)  Global 
D)  Pearson

Question 16

If there are four independent variables in a multiple regression equation, there are also four

Accepted Answer

A)  Y-intercepts. 
B)  regression coeﬃcients. 
C)  dependent variables. 
D)  constant terms. 
A)  Y-intercepts. 
B)  regression coeﬃcients. 
C)  dependent variables. 
D)  constant terms.

Question 17

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:  
The results for the variable gender show that,

Accepted Answer

A)  males average $222.78 more than females in monthly salary. 
B)  females average $222.78 more than males in monthly salary. 
C)  gender is not related to monthly salary. 
D)  gender and months of service are correlated. 
A)  males average $222.78 more than females in monthly salary. 
B)  females average $222.78 more than males in monthly salary. 
C)  gender is not related to monthly salary. 
D)  gender and months of service are correlated.

Question 18

What is the proportion of variation in tires produced by our predictor variables in the model?

Accepted Answer

A)  0.69 
B)  0.83 
C)  0.09 
D)  0.67 
A)  0.69 
B)  0.83 
C)  0.09 
D)  0.67

Question 19

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 1% level of signiﬁcance.
X1 is years of teaching experience, X2 is principal's rating and x3 is the presence of a PhD or not.

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 20

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 and a 0.05 signiﬁcance level, the global null hypothesis test of the multiple
Regression model.

Accepted Answer

A)  will be rejected and conclude that monthly salary is related to all of the independent variables. 
B)  will be rejected and conclude that monthly salary is related to at least one of the independent variables. 
C)  will not be rejected. 
D)  will show a high multiple coeﬃcient of determination. 
A)  will be rejected and conclude that monthly salary is related to all of the independent variables. 
B)  will be rejected and conclude that monthly salary is related to at least one of the independent variables. 
C)  will not be rejected. 
D)  will show a high multiple coeﬃcient of determination.

What is the value of the denominator in the calculation of the multiple standard error of estimate?

If a multiple regression analysis is based on ten independent variables collected from a sample of 125 observations, what will be the value of the denominator in the calculation of the multiple Standard error of estimate?

What can we conclude if the net regression coeﬃcients in the population are not signiﬁcantly Different from zero?

What happens as the scatter of data values about the regression plane increases?

What is the difference in selling prices of a house with 1,600 square feet and one with 1,700 square Feet?

When does multicollinearity occur in a multiple regression analysis?

What does the multiple standard error of estimate measure?

What is the selling price of a house with 1,500 square feet? ______

What is the measurement of explained variation?

If the coeﬃcient of multiple determination is 0.81, what percent of variation is not explained?

Which variable in the model is the least signiﬁcant in predicting tire production?

What test investigates whether all the independent variables have zero net regression coeﬃcients?

If there are four independent variables in a multiple regression equation, there are also four

What is the proportion of variation in tires produced by our predictor variables in the model?

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

What is the value of the denominator in the calculation of the multiple standard error of estimate?

If a multiple regression analysis is based on ten independent variables collected from a sample of 125 observations, what will be the value of the denominator in the calculation of the multiple Standard error of estimate?

What can we conclude if the net regression coeﬃcients in the population are not signiﬁcantly Different from zero?

What happens as the scatter of data values about the regression plane increases?

What is the difference in selling prices of a house with 1,600 square feet and one with 1,700 square Feet?

When does multicollinearity occur in a multiple regression analysis?

What does the multiple standard error of estimate measure?

What is the selling price of a house with 1,500 square feet? ______

What is the measurement of explained variation?

If the coeﬃcient of multiple determination is 0.81, what percent of variation is not explained?

Which variable in the model is the least signiﬁcant in predicting tire production?

What test investigates whether all the independent variables have zero net regression coeﬃcients?

If there are four independent variables in a multiple regression equation, there are also four

What is the proportion of variation in tires produced by our predictor variables in the model?

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