Question 1

Partial regression results from a sample of 12 observations are shown below.Determine the upper bound on the 95% interval estimate of the population slope, β.

Accepted Answer

A) 7.29 
B) 6.63 
C) 5.78 
D) 8.14 
E) 5.26 
A) 7.29 
B) 6.63 
C) 5.78 
D) 8.14 
E) 5.26

Question 2

Suppose you have done a simple linear regression analysis using a sample of 50 data points in an attempt to find a linear connection between worker overtime hours (x) and worker productivity (y) for employees of Sky Marketing Enterprises.The correlation coefficient turned out to be -.80. If total variation in y was 22500, then unexplained variation must be _______.

Accepted Answer

A) 9430 
B) 8100 
C) 6780 
D) 9250 
E) 8710 
A) 9430 
B) 8100 
C) 6780 
D) 9250 
E) 8710

Question 3

In simple linear regression, the variable that will be predicted is labeled the dependent variable.

Accepted Answer

A) True 
 B)False

Question 4

Tennis coach Ben Gordon is trying to identify a linear relationship that can be used to link average first serve velocity to the percent of first serve points won for his junior tennis players.Below is a table showing velocity and percent of points won for a sample of five junior players.   The slope of the least squares line is .44.The intercept is 36.4.Determine the value of R2, the coefficient of determination, that you would insert in the table below.

Accepted Answer

A) .848 
B) .719 
C) .659 
D) .903 
E) .792 
A) .848 
B) .719 
C) .659 
D) .903 
E) .792

Question 5

In simple linear regression, an r2 value of -.93 suggests that:

Accepted Answer

A) there is a fairly strong negative relationship between the variables. 
B) the residual plot will be imprecise. 
C) a computational error has been made. 
D) the value of r (correlation coefficient) will be -.964. 
E) none of the above 
A) there is a fairly strong negative relationship between the variables. 
B) the residual plot will be imprecise. 
C) a computational error has been made. 
D) the value of r (correlation coefficient) will be -.964. 
E) none of the above

Question 6

Suppose you have done a simple linear regression analysis using a sample of 50 data points in an attempt to find a linear connection between worker overtime hours (x) and worker productivity (y) for employees of Sky Marketing Enterprises.The correlation coefficient turned out to be -.80. If total variation in y was 22500, then explained variation (SSR) must be _____.

Accepted Answer

A) 13600 
B) 4300 
C) 4840 
D) 11900 
E) 14400 
A) 13600 
B) 4300 
C) 4840 
D) 11900 
E) 14400

Question 7

Application of the least squares method to regression analysis results in values of the y intercept and the slope that minimizes the sum of the squared deviations between the:

Accepted Answer

A) observed values of the dependent variable and the estimated values of the dependent variable 
B) observed x values and the estimated y values 
C) actual values of the independent variable and the estimated values of the dependent variable 
D) actual values of x and the estimated values of x 
E) none of the above 
A) observed values of the dependent variable and the estimated values of the dependent variable 
B) observed x values and the estimated y values 
C) actual values of the independent variable and the estimated values of the dependent variable 
D) actual values of x and the estimated values of x 
E) none of the above

Question 8

Larger values of r2 imply that the observations are more closely grouped about the:

Accepted Answer

A) mean value of the independent variables 
B) mean value of the dependent variable 
C) least squares line 
D) origin 
E) none of the above 
A) mean value of the independent variables 
B) mean value of the dependent variable 
C) least squares line 
D) origin 
E) none of the above

Question 9

The manager of a local shopping mall uses simple linear regression to develop an equation that predicts the number of daily shoplifting incidents at the mall's stores based on the number of security guards employed.Below is a partial table showing the data that was used.   The slope of the regression line is b = -1.2; the intercept of the regression line is a = 14.5.
Calculate the residual associated with the first observation in the data set, where x = 4 and y = 10.

Accepted Answer

A) -2.03 
B) -2.30 
C) 0.30 
D) 2.30 
A) -2.03 
B) -2.30 
C) 0.30 
D) 2.30

Question 10

A local shopping mall would like to better understand the effectiveness of its security guards in preventing shoplifting.The mall's operation manager uses simple linear regression to develop an equation that predicts the number of daily shoplifting incidents at the mall's stores based on the number of security guards employed.   The slope of the regression line is b = -1.2; the intercept of the regression line is a = 14.5.Compute the value of the standard error of the estimate.

Accepted Answer

A) 0.52 
B) 0.68 
C) 0.82 
D) 2.15 
A) 0.52 
B) 0.68 
C) 0.82 
D) 2.15

Question 11

A regression analysis linking demand (y in 1000 units) and price (x in $) resulted in the following equation: estimated Y = 9 - 3x.This equation implies that if the price is decreased by $1, demand can be expected to:

Accepted Answer

A) increase by 9,000 units 
B) decrease by 9,000 units 
C) decrease by 3,000 units 
D) increase by 3,000 units 
E) none of the above 
A) increase by 9,000 units 
B) decrease by 9,000 units 
C) decrease by 3,000 units 
D) increase by 3,000 units 
E) none of the above

Question 12

Lillian Chernov is trying to identify a linear relationship that can be used to estimate the construction cost for a new sports complex that her construction company is bidding on.Below is a table showing construction costs and floor area for a sample of five similar buildings in the area.   The slope for the least squares line is 4.4.The intercept is 408.Compute the "explained variation" (SSR) here.

Accepted Answer

A) 58080 
B) 62365 
C) 39267 
D) 51256 
E) 49241 
A) 58080 
B) 62365 
C) 39267 
D) 51256 
E) 49241

Question 13

In simple linear regression, rejecting the $\beta$= 0 null hypothesis in the key hypothesis test means:

Accepted Answer

A) we haven't yet found sufficient sample evidence that there's a useful linear relationship between x and y. 
B) we have sufficient sample evidence that there's no useful linear relationship between x and y. 
C) there is convincing sample evidence of a useful linear relationship between x and y. 
D) the sum of the residuals is such that no linear relationship can be established between x and y. 
E) that the p-value is greater than alpha. 
A) we haven't yet found sufficient sample evidence that there's a useful linear relationship between x and y. 
B) we have sufficient sample evidence that there's no useful linear relationship between x and y. 
C) there is convincing sample evidence of a useful linear relationship between x and y. 
D) the sum of the residuals is such that no linear relationship can be established between x and y. 
E) that the p-value is greater than alpha.

Question 14

The regression printout below shows the results of a regression analysis intended to link company profits (x) to CEO salary (y).A sample of 18 CEOs was used.Based on the printout provided, what proportion of the variation in income CANNOT be explained by the profit-to-salary relationship represented by the estimated regression line?

Accepted Answer

A) .082 
B) .106 
C) .391 
D) .048 
E) .024 
A) .082 
B) .106 
C) .391 
D) .048 
E) .024

Question 15

A National football League agent is conducting a simple linear regression study linking passes caught in a season (x) to annual salary (y) for wide receivers in the league.The data for five players are shown below.   The slope for the least squares line is 2.2.The intercept is 182.Compute the standard error of estimate (sy.x) here.

Accepted Answer

A) 116.34 
B) 67.82 
C) 43.51 
D) 18.19 
E) 21.68 
A) 116.34 
B) 67.82 
C) 43.51 
D) 18.19 
E) 21.68

Question 16

In simple regression, the usual goal is to identify a cause-and-effect relationship between two variables.

Accepted Answer

A) True 
 B)False

Question 17

You are using linear regression to link number of responses to a job announcement (y) to the number of days the announcement was repeated (x):   In applying the least squares criterion, the slope (b) and the intercept (a) for the best-fitting line are b = 1.0 and a = 3.5.Produce the 95% confidence interval estimate of the population intercept and report the upper bound for your interval.

Accepted Answer

A) 4.5 
B) 9.7 
C) 8.3 
D) 6.1 
E) 7.2 
A) 4.5 
B) 9.7 
C) 8.3 
D) 6.1 
E) 7.2

Question 18

The following data have been collected for a simple linear regression analysis:   In applying the least squares criterion, the slope (b) and the intercept (a) for the best-fitting line are b = 1.4 and a = .2.Compute the value of r2 here.

Accepted Answer

A) .65 
B) .23 
C) .58 
D) .36 
E) .70 
A) .65 
B) .23 
C) .58 
D) .36 
E) .70

Question 19

Preston Gomez is attempting to identify a linear relationship that will link heating and air conditioning costs to total floor area for his commercial properties.Below is a table showing heating /AC costs and floor area for five buildings in the area.   The computer output table below shows partial results for the linear regression analysis done here.Determine the upper bound on a 95% confidence interval estimate of the slope in the regression equation-a value that would be entered in the indicated cell of the output table.

Accepted Answer

A) 3.56 
B) 5.14 
C) 4.21 
D) 3.19 
E) 4.73 
A) 3.56 
B) 5.14 
C) 4.21 
D) 3.19 
E) 4.73

Question 20

Needing a simple cost estimator for commercial construction costs in the city, you hope to find a useful linear relationship between cost (y) and floor space (x).You have data from a sample of four recently completed building projects:   The estimated regression equation turns out to be y = 24 + 1.6x and sb= 1.13.Construct an appropriate hypothesis test to determine whether we can use the sample data here to reject a β = 0 null hypothesis at the 5% significance level.Report your conclusion.

Accepted Answer

A) Since tstat is outside the critical values of ±3.182, we can reject the β=0 null hypothesis. 
B) Since tstat is outside the critical values of ±4.362, we can reject the β=0 null hypothesis. 
C) Since tstat is not outside the critical values of ±4.303, we can't reject the β=0 null hypothesis. 
D) Since tstat is not outside the critical values of ±2.182, we can't reject the β=0 null hypothesis. 
A) Since tstat is outside the critical values of ±3.182, we can reject the β=0 null hypothesis. 
B) Since tstat is outside the critical values of ±4.362, we can reject the β=0 null hypothesis. 
C) Since tstat is not outside the critical values of ±4.303, we can't reject the β=0 null hypothesis. 
D) Since tstat is not outside the critical values of ±2.182, we can't reject the β=0 null hypothesis.

Partial regression results from a sample of 12 observations are shown below.Determine the upper bound on the 95% interval estimate of the population slope, β.

In simple linear regression, the variable that will be predicted is labeled the dependent variable.

In simple linear regression, an r² value of -.93 suggests that:

Application of the least squares method to regression analysis results in values of the y intercept and the slope that minimizes the sum of the squared deviations between the:

Larger values of r² imply that the observations are more closely grouped about the:

A regression analysis linking demand (y in 1000 units) and price (x in $) resulted in the following equation: estimated Y = 9 - 3x.This equation implies that if the price is decreased by $1, demand can be expected to:

In simple linear regression, rejecting the $\beta$ = 0 null hypothesis in the key hypothesis test means:

In simple regression, the usual goal is to identify a cause-and-effect relationship between two variables.

The following data have been collected for a simple linear regression analysis: In applying the least squares criterion, the slope (b) and the intercept (a) for the best-fitting line are b = 1.4 and a = .2.Compute the value of r² here.

An Introduction to Statistics

Descriptive Statistics I: Elementary Data Presentation and Description

Descriptive Statistics II: Additional Descriptive Measures and Data Displays

Probability

Discrete Probability Distributions

Continuous Probability Distributions

Statistical Inference: Estimating a Population Mean

Interval Estimates for Proportions, Mean Differences and Proportion Differences

Statistical Hypothesis Testing: Hypothesis Tests for a Population Mean

Hypothesis Tests for Proportions, Mean Differences and Proportion Differences

Multiple Regression

F Tests and Analysis of Variance

Experimental Designonline Only

Chi-Square Tests

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Exam 11: Basic Regression Analysis

Partial regression results from a sample of 12 observations are shown below.Determine the upper bound on the 95% interval estimate of the population slope, β.

In simple linear regression, the variable that will be predicted is labeled the dependent variable.

In simple linear regression, an r2 value of -.93 suggests that:

Application of the least squares method to regression analysis results in values of the y intercept and the slope that minimizes the sum of the squared deviations between the:

Larger values of r2 imply that the observations are more closely grouped about the:

A regression analysis linking demand (y in 1000 units) and price (x in $) resulted in the following equation: estimated Y = 9 - 3x.This equation implies that if the price is decreased by $1, demand can be expected to:

In simple linear regression, rejecting the β\betaβ = 0 null hypothesis in the key hypothesis test means:

In simple regression, the usual goal is to identify a cause-and-effect relationship between two variables.

The following data have been collected for a simple linear regression analysis: In applying the least squares criterion, the slope (b) and the intercept (a) for the best-fitting line are b = 1.4 and a = .2.Compute the value of r2 here.

An Introduction to Statistics

Descriptive Statistics I: Elementary Data Presentation and Description

Descriptive Statistics II: Additional Descriptive Measures and Data Displays

Probability

Discrete Probability Distributions

Continuous Probability Distributions

Statistical Inference: Estimating a Population Mean

Interval Estimates for Proportions, Mean Differences and Proportion Differences

Statistical Hypothesis Testing: Hypothesis Tests for a Population Mean

Hypothesis Tests for Proportions, Mean Differences and Proportion Differences

Multiple Regression

F Tests and Analysis of Variance

Experimental Designonline Only

Chi-Square Tests

Filters

In simple linear regression, an r² value of -.93 suggests that:

Larger values of r² imply that the observations are more closely grouped about the:

In simple linear regression, rejecting the $\beta$ = 0 null hypothesis in the key hypothesis test means:

The following data have been collected for a simple linear regression analysis: In applying the least squares criterion, the slope (b) and the intercept (a) for the best-fitting line are b = 1.4 and a = .2.Compute the value of r² here.