Question 1

When a pair of variables has a positive correlation,the slope in the regression equation will always be positive.

Accepted Answer

A) True 
 B)False

Question 2

Which of the following statements is true with respect to a simple linear regression model?

Accepted Answer

A) The regression slope coefficient is the square of the correlation coefficient. 
B) The percentage of variation in the dependent variable that is explained by the independent variable can be determined by squaring the correlation coefficient. 
C) It is possible that the correlation between a y and x variable might be statistically significant,but the regression slope coefficient could be determined to be zero since they measure different things. 
D) The standard error of the estimate is equal to the standard error of the slope. 
A) The regression slope coefficient is the square of the correlation coefficient. 
B) The percentage of variation in the dependent variable that is explained by the independent variable can be determined by squaring the correlation coefficient. 
C) It is possible that the correlation between a y and x variable might be statistically significant,but the regression slope coefficient could be determined to be zero since they measure different things. 
D) The standard error of the estimate is equal to the standard error of the slope.

Question 3

Which of the following statements is true?

Accepted Answer

A) When using a simple linear regression analysis model for prediction purposes,the potential error in the forecast will be less when the value of x used to forecast y is closer to  
. 
B) The accuracy of the regression forecast is improved if the standard error for the regression slope coefficient is reduced. 
C) The use of regression analysis as a means of predicting the value for a dependent variable is not impacted by sampling error since the regression model uses all sample data to arrive at the regression model. 
D) None of the above 
A) When using a simple linear regression analysis model for prediction purposes,the potential error in the forecast will be less when the value of x used to forecast y is closer to  
. 
B) The accuracy of the regression forecast is improved if the standard error for the regression slope coefficient is reduced. 
C) The use of regression analysis as a means of predicting the value for a dependent variable is not impacted by sampling error since the regression model uses all sample data to arrive at the regression model. 
D) None of the above

Question 4

In a simple regression model,the slope coefficient represents the average change in the independent variable for a one-unit change in the dependent variable.

Accepted Answer

A) True 
 B)False

Question 5

If two variables are highly correlated,it not only means that they are linearly related,it also means that a change in one variable will cause a change in the other variable.

Accepted Answer

A) True 
 B)False

Question 6

It is believed that number of people who attend a Mardi Gras parade each year depends on the temperature that day.A regression has been conducted on a sample of years where the temperature ranged from 28 to 64 degrees and the number of people attending ranged from 8400 to 14,600.The regression equation was found to be   = 2378 + 191x.Which of the following is true?

Accepted Answer

A) The average change in parade attendance is an additional 2378 people per one-degree increase in temperature. 
B) The average change in parade attendance is an additional 191 people per one-degree increase in temperature. 
C) If the temperature is 75 degrees,we can expect that 16,703 people will attend. 
D) If the temperature is 0 degrees this year,then we should expect 2378 people to attend. 
A) The average change in parade attendance is an additional 2378 people per one-degree increase in temperature. 
B) The average change in parade attendance is an additional 191 people per one-degree increase in temperature. 
C) If the temperature is 75 degrees,we can expect that 16,703 people will attend. 
D) If the temperature is 0 degrees this year,then we should expect 2378 people to attend.

Question 7

Explain what is meant by the term least squares regression model.

Accepted Answer

When we look at a scatter plot,we see th

Question 8

When calculating prediction intervals for predicted values of y based on a given x,all 95 percent prediction intervals will be of equal width.

Accepted Answer

A) True 
 B)False

Question 9

In a simple linear regression analysis,if the test statistic for testing the significance of the regression slope coefficient is 3.6,the F ratio from the analysis of variance table is known to be 12.96

Accepted Answer

A) True 
 B)False

Question 10

Consider the following partially completed computer printout for a regression analysis where the dependent variable is the price of a personal computer and the independent variable is the size of the hard drive.   Based on the information provided,what is the estimate for the standard error of the estimate for the regression model?

Accepted Answer

A) Approximately 690.50 
B) About 4,026 
C) Just under 376.23 
D) 476,800 
A) Approximately 690.50 
B) About 4,026 
C) Just under 376.23 
D) 476,800

Question 11

The following regression output was generated based on a sample of utility customers.The dependent variable was the dollar amount of the monthly bill and the independent variable was the size of the house in square feet.   Based on this regression output,which of the following statements is not true?

Accepted Answer

A) The number of square feet in the house explains only about 2 percent of the variation in the monthly power bill. 
B) At an alpha level equal to 0.05,there is no basis for rejecting the hypothesis that the slope coefficient is equal to zero. 
C) The average increase in the monthly power bill is about 66.4 for each additional square foot of space in the house. 
D) The correlation of the monthly power bill with the square footage of the house is 0.149 
A) The number of square feet in the house explains only about 2 percent of the variation in the monthly power bill. 
B) At an alpha level equal to 0.05,there is no basis for rejecting the hypothesis that the slope coefficient is equal to zero. 
C) The average increase in the monthly power bill is about 66.4 for each additional square foot of space in the house. 
D) The correlation of the monthly power bill with the square footage of the house is 0.149

Question 12

A regression model that is deemed to have a regression slope coefficient that could be equal to zero should not be used for prediction since there is no established linear relationship between the x and y variable.

Accepted Answer

A) True 
 B)False

Question 13

In developing a scatter plot,the decision maker has the option of connecting the points or not.

Accepted Answer

A) True 
 B)False

Question 14

State University recently randomly sampled ten students and analyzed grade point average (GPA)and number of hours worked off-campus per week.The following data were observed:
   In this study the independent variable is the number of hours worked off campus per week.

Accepted Answer

A) True 
 B)False

Question 15

The prediction interval developed from a simple linear regression model will be at its narrowest point when the value of x used to predict y is equal to the mean value of x.

Accepted Answer

A) True 
 B)False

Question 16

A recent study of 15 shoppers showed that the correlation between the time spent in the store and the dollars spent was 0.235.Using a significance level equal to 0.05,which of the following is true?

Accepted Answer

A) The null hypothesis that the population mean is equal to zero should be rejected and we should conclude that the true correlation is not equal to zero. 
B) Based on the sample data there is not enough evidence to conclude that the true correlation is different from zero. 
C) The sample correlation coefficient could be zero since the test statistic does not fall in the rejection region. 
D) The null hypothesis should be rejected because the test statistic exceeds the critical value. 
A) The null hypothesis that the population mean is equal to zero should be rejected and we should conclude that the true correlation is not equal to zero. 
B) Based on the sample data there is not enough evidence to conclude that the true correlation is different from zero. 
C) The sample correlation coefficient could be zero since the test statistic does not fall in the rejection region. 
D) The null hypothesis should be rejected because the test statistic exceeds the critical value.

Question 17

Consider the following partially completed computer printout for a regression analysis where the dependent variable is the price of a personal computer and the independent variable is the size of the hard drive.   Based on the information provided,what is the F statistic?

Accepted Answer

A) About 8 .33 
B) Just over 2.35 
C) About 4.76 
D) About 69.5 
A) About 8 .33 
B) Just over 2.35 
C) About 4.76 
D) About 69.5

Question 18

You are given the following sample data for two variables:
   The regression model based on these sample data explains approximately 75 percent of the variation in the dependent variable.

Accepted Answer

A) True 
 B)False

Question 19

Assuming that a regression has been conducted for a group of small companies where x = the number of employees at the company,y = annual revenue of the company (recorded in thousands of dollars),and the largest company included in the study had 82 employees.The resulting regression equation is   = 59.2 + 83.4x.Which of the following is true?

Accepted Answer

A) For each additional employee,revenue on average will increase by $83.4 
B) A company with 2100 employees could be predicted to have average revenue of about $175 million. 
C) For each additional employee,revenue on average will increase by $59.2 thousand. 
D) This model should not be used to make predictions for companies with more than 82 employees. 
A) For each additional employee,revenue on average will increase by $83.4 
B) A company with 2100 employees could be predicted to have average revenue of about $175 million. 
C) For each additional employee,revenue on average will increase by $59.2 thousand. 
D) This model should not be used to make predictions for companies with more than 82 employees.

Question 20

A perfect correlation between two variables will always produce a correlation coefficient of +1.0

Accepted Answer

A) True 
 B)False

When a pair of variables has a positive correlation,the slope in the regression equation will always be positive.

Which of the following statements is true with respect to a simple linear regression model?

Which of the following statements is true?

In a simple regression model,the slope coefficient represents the average change in the independent variable for a one-unit change in the dependent variable.

If two variables are highly correlated,it not only means that they are linearly related,it also means that a change in one variable will cause a change in the other variable.

Explain what is meant by the term least squares regression model.

When calculating prediction intervals for predicted values of y based on a given x,all 95 percent prediction intervals will be of equal width.

In a simple linear regression analysis,if the test statistic for testing the significance of the regression slope coefficient is 3.6,the F ratio from the analysis of variance table is known to be 12.96

The following regression output was generated based on a sample of utility customers.The dependent variable was the dollar amount of the monthly bill and the independent variable was the size of the house in square feet. Based on this regression output,which of the following statements is not true?

A regression model that is deemed to have a regression slope coefficient that could be equal to zero should not be used for prediction since there is no established linear relationship between the x and y variable.

In developing a scatter plot,the decision maker has the option of connecting the points or not.

State University recently randomly sampled ten students and analyzed grade point average (GPA)and number of hours worked off-campus per week.The following data were observed: In this study the independent variable is the number of hours worked off campus per week.

The prediction interval developed from a simple linear regression model will be at its narrowest point when the value of x used to predict y is equal to the mean value of x.

A recent study of 15 shoppers showed that the correlation between the time spent in the store and the dollars spent was 0.235.Using a significance level equal to 0.05,which of the following is true?

Consider the following partially completed computer printout for a regression analysis where the dependent variable is the price of a personal computer and the independent variable is the size of the hard drive. Based on the information provided,what is the F statistic?

You are given the following sample data for two variables: The regression model based on these sample data explains approximately 75 percent of the variation in the dependent variable.

A perfect correlation between two variables will always produce a correlation coefficient of +1.0

The Where,Why,and How of Data Collection

Graphs,Charts and Tablesdescribing Your Data

Describing Data Using Numerical Measures

Introduction to Probability

Discrete Probability Distributions

Introduction to Continuous Probability Distributions

Introduction to Sampling Distributions

Estimating Single Population Parameters

Introduction to Hypothesis Testing

Estimation and Hypothesis Testing for Two Population Parameters

Hypothesis Tests and Estimation for Population Variances

Analysis of Variance

Goodness-Of-Fit Tests and Contingency Analysis

Multiple Regression Analysis and Model Building

Analyzing and Forecasting Time-Series Data

Introduction to Nonparametric Statistics

Introduction to Quality and Statistical Process Control

Filters

Exam 14: Introduction to Linear Regression and Correlation Analysis

When a pair of variables has a positive correlation,the slope in the regression equation will always be positive.

Which of the following statements is true with respect to a simple linear regression model?

Which of the following statements is true?

In a simple regression model,the slope coefficient represents the average change in the independent variable for a one-unit change in the dependent variable.

If two variables are highly correlated,it not only means that they are linearly related,it also means that a change in one variable will cause a change in the other variable.

Explain what is meant by the term least squares regression model.

When calculating prediction intervals for predicted values of y based on a given x,all 95 percent prediction intervals will be of equal width.

In a simple linear regression analysis,if the test statistic for testing the significance of the regression slope coefficient is 3.6,the F ratio from the analysis of variance table is known to be 12.96

The following regression output was generated based on a sample of utility customers.The dependent variable was the dollar amount of the monthly bill and the independent variable was the size of the house in square feet. Based on this regression output,which of the following statements is not true?

A regression model that is deemed to have a regression slope coefficient that could be equal to zero should not be used for prediction since there is no established linear relationship between the x and y variable.

In developing a scatter plot,the decision maker has the option of connecting the points or not.

State University recently randomly sampled ten students and analyzed grade point average (GPA)and number of hours worked off-campus per week.The following data were observed: In this study the independent variable is the number of hours worked off campus per week.

The prediction interval developed from a simple linear regression model will be at its narrowest point when the value of x used to predict y is equal to the mean value of x.

A recent study of 15 shoppers showed that the correlation between the time spent in the store and the dollars spent was 0.235.Using a significance level equal to 0.05,which of the following is true?

Consider the following partially completed computer printout for a regression analysis where the dependent variable is the price of a personal computer and the independent variable is the size of the hard drive. Based on the information provided,what is the F statistic?

You are given the following sample data for two variables: The regression model based on these sample data explains approximately 75 percent of the variation in the dependent variable.

A perfect correlation between two variables will always produce a correlation coefficient of +1.0

The Where,Why,and How of Data Collection

Graphs,Charts and Tablesdescribing Your Data

Describing Data Using Numerical Measures

Introduction to Probability

Discrete Probability Distributions

Introduction to Continuous Probability Distributions

Introduction to Sampling Distributions

Estimating Single Population Parameters

Introduction to Hypothesis Testing

Estimation and Hypothesis Testing for Two Population Parameters

Hypothesis Tests and Estimation for Population Variances

Analysis of Variance

Goodness-Of-Fit Tests and Contingency Analysis

Multiple Regression Analysis and Model Building

Analyzing and Forecasting Time-Series Data

Introduction to Nonparametric Statistics

Introduction to Quality and Statistical Process Control

Filters