Question 1

Given that the sum of squares for error is 60 and the sum of squares for regression is 140,then the coefficient of determination is:

Accepted Answer

A) 0.429 
B) 0.300 
C) 0.700 
D) None of these choices. 
A) 0.429 
B) 0.300 
C) 0.700 
D) None of these choices. C

Question 2

In simple linear regression,which of the following statements indicates there is no linear relationship between the variables x and y?

Accepted Answer

A) Coefficient of determination is −1.0. 
B) Coefficient of correlation is 0.0. 
C) Sum of squares for error is 0.0. 
D) None of these choices. 
A) Coefficient of determination is −1.0. 
B) Coefficient of correlation is 0.0. 
C) Sum of squares for error is 0.0. 
D) None of these choices. B

Question 3

If the coefficient of correlation between x and y is close to 1.0,this indicates that:

Accepted Answer

A) y causes x to happen. 
B)  x causes y to happen. 
C)  Both a and b. 
D)  there may or may not be a causal relationship between x and y. 
A) y causes x to happen. 
B)  x causes y to happen. 
C)  Both a and b. 
D)  there may or may not be a causal relationship between x and y. D

Question 4

In regression analysis,you predict the value of one variable on the basis of one or more other related variables.The variable being predicted is called the ____________________ variable,and the related variables used to make the prediction are called ____________________ variables.

Accepted Answer

dependent;

Question 5

Sunshine and Melanoma
 A medical researcher wanted to examine the relationship between the amount of sunshine (x)in hours,and incidence of melanoma,a type of skin cancer (y).As an experiment he found the number of melanoma cases detected per 100,000 of population and the average daily sunshine in eight counties around the country.These data are shown below.   ​ ​
-{Sunshine and Melanoma Narrative} What does the value of the slope of the regression line tell you?

Accepted Answer

If the amount of sunshine x in

Question 6

The variance of the error variable   is required to be constant.When this requirement is violated,the condition is called heteroscedasticity.

Accepted Answer

A) True 
 B)False

Question 7

Data that exhibit an autocorrelation effect violate the regression assumption of independence.

Accepted Answer

A) True 
 B)False

Question 8

A regression analysis between weight (y in pounds)and height (x in inches)resulted in the following least squares line:   .This implies that if the height is increased by 1 inch,the weight is expected to increase by an average of 6 pounds.

Accepted Answer

A) True 
 B)False

Question 9

Correlation analysis is used to determine whether there is a linear relationship between an independent variable x and a dependent variable y.

Accepted Answer

A) True 
 B)False

Question 10

Trivia Games & Education
 An ardent fan of television game shows has observed that,in general,the more educated the contestant,the less money he or she wins.To test her belief she gathers data about the last eight winners of her favorite game show.She records their winnings in dollars and the number of years of education.The results are as follows.   ​ ​
-{Trivia Games & Education Narrative} Estimate the game winnings for a contestant with 15 years of education.

Accepted Answer

The answer of Trivia Games & Education
 An ardent fan...

Question 11

Marc Anthony Concert
 At a recent Marc Anthony concert,a survey was conducted that asked a random sample of 20 people their age and how many concerts they have attended since the first of the year.The following data were collected:   An Excel output follows:   ​ ​
-{Marc Anthony Concert Narrative} Draw a histogram of the residuals.

Accepted Answer

The answer of Marc Anthony Concert
 At a recent Marc...

Question 12

In the first order linear regression model,the population parameters of the y-intercept and the slope are estimated,respectively,by:

Accepted Answer

A) b0 and b1 
B) b0 and β1 
C) β0 and b1 
D) β0 and β1 
A) b0 and b1 
B) b0 and β1 
C) β0 and b1 
D) β0 and β1

Question 13

A scatter diagram includes the following data points:   Two regression models are proposed: (1)   ,and (2)   .Using the least squares method,which of these regression models provides the better fit to the data? Why?

Accepted Answer

SSE = 4.95 and 156 for models

Question 14

In order to predict with 90% confidence the expected value of y for a given value of x in a simple linear regression problem,a random sample of 10 observations is taken.Which of the following t-table values listed below would be used?

Accepted Answer

A) 1.812 
B) 1.860 
C) 2.228 
D) 2.306 
A) 1.812 
B) 1.860 
C) 2.228 
D) 2.306

Question 15

Theatre Revenues 
A financier whose specialty is investing in stage productions has observed that,in general,movies with "big-name" stars seem to generate more revenue than those plays whose stars are less well known.To examine his belief he records the gross revenue and the payment (in $ millions)given to the two highest-paid performers in the play for ten recently staged plays.   ​ ​
-{Theatre Revenues Narrative} Interpret the value of the slope of the regression line.

Accepted Answer

For each million dollars paid

Question 16

Trivia Games & Education
 An ardent fan of television game shows has observed that,in general,the more educated the contestant,the less money he or she wins.To test her belief she gathers data about the last eight winners of her favorite game show.She records their winnings in dollars and the number of years of education.The results are as follows.   ​ ​
-{Trivia Games & Education Narrative} Interpret the value of the slope of the regression line.

Accepted Answer

For each additional year of ed

Question 17

There is more error in estimating a mean value of y as opposed to predicting an individual value of y.

Accepted Answer

A) True 
 B)False

Question 18

Oil Quality and Price
Quality of oil is measured in API gravity degrees--the higher the degrees API, the higher the quality. The table shown below is produced by an expert in the field who believes that there is a relationship between quality and price per barrel.
 
A partial Minitab output follows:

-{Oil Quality and Price Narrative} Conduct a test of the population slope to determine at the 5% significance level whether a linear relationship exists between the quality of oil and price per barrel.

Accepted Answer

H₀: β₁ = 0 vs.H₁: β₁ > 0 Rejection region: t

Question 19

If the coefficient of correlation is −0.60,then the coefficient of determination is:

Accepted Answer

A) −0.60 
B) −0.36 
C) 0.36 
D) 0.77 
A) −0.60 
B) −0.36 
C) 0.36 
D) 0.77

Question 20

If a single point has a large impact on the equation of the regression line,it is called a(n)____________________ point.

Accepted Answer

The answer of If a single point has a large...

Given that the sum of squares for error is 60 and the sum of squares for regression is 140,then the coefficient of determination is:

In simple linear regression,which of the following statements indicates there is no linear relationship between the variables x and y?

If the coefficient of correlation between x and y is close to 1.0,this indicates that:

In regression analysis,you predict the value of one variable on the basis of one or more other related variables.The variable being predicted is called the variable,and the related variables used to make the prediction are called variables.

The variance of the error variable is required to be constant.When this requirement is violated,the condition is called heteroscedasticity.

Data that exhibit an autocorrelation effect violate the regression assumption of independence.

A regression analysis between weight (y in pounds)and height (x in inches)resulted in the following least squares line: .This implies that if the height is increased by 1 inch,the weight is expected to increase by an average of 6 pounds.

Correlation analysis is used to determine whether there is a linear relationship between an independent variable x and a dependent variable y.

In the first order linear regression model,the population parameters of the y-intercept and the slope are estimated,respectively,by:

A scatter diagram includes the following data points: Two regression models are proposed: (1) ,and (2) .Using the least squares method,which of these regression models provides the better fit to the data? Why?

In order to predict with 90% confidence the expected value of y for a given value of x in a simple linear regression problem,a random sample of 10 observations is taken.Which of the following t-table values listed below would be used?

There is more error in estimating a mean value of y as opposed to predicting an individual value of y.

If the coefficient of correlation is −0.60,then the coefficient of determination is:

If a single point has a large impact on the equation of the regression line,it is called a(n)____________________ point.

What Is Statistics

Graphical Descriptive Techniques 1

Graphical Descriptive Techniques 2

Numerical Descriptive Techniques

Data Collection and Sampling

Probability

Random Variables and Discrete Probability Distributions

Continuous Probability Distributions

Sampling Distributions

Introduction to Estimation

Introduction to Hypothesis Testing

Inference About a Population

Inference About Comparing Two Populations

Analysis of Variance

Chi-Squared Tests

Multiple Regression

Model Building

Nonparametric Statistics

Time-Series Analytics and Forecasting

Statistical Process Control

Decision Analysis

Conclusion

Filters

Exam 16: Simple Linear Regression and Correlation

Given that the sum of squares for error is 60 and the sum of squares for regression is 140,then the coefficient of determination is:

In simple linear regression,which of the following statements indicates there is no linear relationship between the variables x and y?

If the coefficient of correlation between x and y is close to 1.0,this indicates that:

In regression analysis,you predict the value of one variable on the basis of one or more other related variables.The variable being predicted is called the ____________________ variable,and the related variables used to make the prediction are called ____________________ variables.

The variance of the error variable is required to be constant.When this requirement is violated,the condition is called heteroscedasticity.

Data that exhibit an autocorrelation effect violate the regression assumption of independence.

A regression analysis between weight (y in pounds)and height (x in inches)resulted in the following least squares line: .This implies that if the height is increased by 1 inch,the weight is expected to increase by an average of 6 pounds.

Correlation analysis is used to determine whether there is a linear relationship between an independent variable x and a dependent variable y.

In the first order linear regression model,the population parameters of the y-intercept and the slope are estimated,respectively,by:

A scatter diagram includes the following data points: Two regression models are proposed: (1) ,and (2) .Using the least squares method,which of these regression models provides the better fit to the data? Why?

In order to predict with 90% confidence the expected value of y for a given value of x in a simple linear regression problem,a random sample of 10 observations is taken.Which of the following t-table values listed below would be used?

There is more error in estimating a mean value of y as opposed to predicting an individual value of y.

If the coefficient of correlation is −0.60,then the coefficient of determination is:

If a single point has a large impact on the equation of the regression line,it is called a(n)____________________ point.

What Is Statistics

Graphical Descriptive Techniques 1

Graphical Descriptive Techniques 2

Numerical Descriptive Techniques

Data Collection and Sampling

Probability

Random Variables and Discrete Probability Distributions

Continuous Probability Distributions

Sampling Distributions

Introduction to Estimation

Introduction to Hypothesis Testing

Inference About a Population

Inference About Comparing Two Populations

Analysis of Variance

Chi-Squared Tests

Multiple Regression

Model Building

Nonparametric Statistics

Time-Series Analytics and Forecasting

Statistical Process Control

Decision Analysis

Conclusion

Filters

In regression analysis,you predict the value of one variable on the basis of one or more other related variables.The variable being predicted is called the variable,and the related variables used to make the prediction are called variables.