Question 1

Analyze the residual lot below. Does it violate any of the conditions for an adequate linear model?
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Accepted Answer

A)  No, the plot of residuals is random. 
B)  Yes, the residuals do not display constant error variance. 
C)  Yes, there is a discernable pattern in the residuals. 
A)  No, the plot of residuals is random. 
B)  Yes, the residuals do not display constant error variance. 
C)  Yes, there is a discernable pattern in the residuals.

Question 2

Compute the linear correlation coefficient between the two variables and determine whether a linear relation exists.
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Accepted Answer

A)  r = 0.708; no linear relation exists 
B)  r = 0.235; no linear relation exists 
C)  r = 0.708; linear relation exists 
D)  r = -0.708; linear relation exists 
A)  r = 0.708; no linear relation exists 
B)  r = 0.235; no linear relation exists 
C)  r = 0.708; linear relation exists 
D)  r = -0.708; linear relation exists

Question 3

A county real estate appraiser wants to develop a statistical model to predict the appraised value of houses in a section of the county called East Meadow. One of the many variables thought to be an important predictor of appraised value is the number of rooms in the house. Consequently, the appraiser decided to fit the simple linear regression model,   where y = appraised value of the house (in $thousands) and x = number of rooms. Using data collected for a sample of n= 74 houses in East Meadow, the following results were obtained:   Give a practical interpretation of the estimate of the y-intercept of the least squares line.

Accepted Answer

A)  For each additional room in the house, we estimate the appraised value to increase $19,720. 
B)  For each additional room in the house, we estimate the appraised value to increase $74,800. 
C)  There is no practical interpretation, since a house with 0 rooms is nonsensical. 
D)  We estimate the base appraised value for any house to be $74,800. 
A)  For each additional room in the house, we estimate the appraised value to increase $19,720. 
B)  For each additional room in the house, we estimate the appraised value to increase $74,800. 
C)  There is no practical interpretation, since a house with 0 rooms is nonsensical. 
D)  We estimate the base appraised value for any house to be $74,800.

Question 4

The data below show the age and favorite type of music of 779 randomly selected people. Use   What, if any, association exists between favorite music and age? Discuss the association.

Accepted Answer

The proportion who prefers country music

Question 5

Construct a scatter diagram for the data.
-The scores of nine members of a local community college women's golf team in two rounds of tournament play are listed below.

Accepted Answer

The answer of Construct a scatter diagram for the data.
-The...

Question 6

In an area of Russia, records were kept on the relationship between the rainfall (in inches) and the yield of wheat (bushels per acre). The data for a 9 year period is as follows:   The equation of the line of least squares is given as   = -9.12 + 4.38x.
- How many bushels of wheat per acre can be predicted if it is expected that there will be 30 inches of rain?

Accepted Answer

A)  Cannot be certain of the result because 30 inches of rain exceeds the observed data. 
B)  8.93 
C)  122.28 
D)  140.52 
A)  Cannot be certain of the result because 30 inches of rain exceeds the observed data. 
B)  8.93 
C)  122.28 
D)  140.52

Question 7

Is there a relationship between the raises administrators at State University receive and their performance on the job? A faculty group wants to determine whether job rating (x) is a useful linear predictor of raise (y). Consequently, the group considered the straight-line regression model,   Using the method of least squares, the faculty group obtained the following prediction equation,   Interpret the estimated slope of the line.

Accepted Answer

A)  For a $1 increase in an administrator's raise, we estimate the administrator's rating to decrease 2,000 points. 
B)  For a 1-point increase in an administrator's rating, we estimate the administrator's raise to decrease $2,000. 
C)  For a 1-point increase in an administrator's rating, we estimate the administrator's raise to increase $2,000. 
D)  For an administrator with a rating of 1.0, we estimate his/her raise to be $2,000. 
A)  For a $1 increase in an administrator's raise, we estimate the administrator's rating to decrease 2,000 points. 
B)  For a 1-point increase in an administrator's rating, we estimate the administrator's raise to decrease $2,000. 
C)  For a 1-point increase in an administrator's rating, we estimate the administrator's raise to increase $2,000. 
D)  For an administrator with a rating of 1.0, we estimate his/her raise to be $2,000.

Question 8

Civil engineers often use the straight-line equation, E(y) =   +   x, to model the relationship between the mean shear strength E(y) of masonry joints and precompression stress, x. To test this theory, a series of stress tests were performed on solid bricks arranged in triplets and joined with mortar. The precompression stress was varied for each triplet and the ultimate shear load just before failure (called the shear strength) was recorded. The stress results for n = 7 triplet tests is shown in the accompanying table followed by a SAS printout of the regression analysis.

Accepted Answer

A)  In repeated sampling, approximately 91% of all similarly constructed regression lines will accurately predict shear strength. 
B)  About 91% of the total variation in the sample of y-values can be explained by (or attributed to) the linear relationship between shear strength and precompression stress. 
C)  We expect about 91% of the observed shear strength values to lie on the least squares line. 
D)  We expect to predict the shear strength of a triplet test to within about .91 ton of its true value. 
A)  In repeated sampling, approximately 91% of all similarly constructed regression lines will accurately predict shear strength. 
B)  About 91% of the total variation in the sample of y-values can be explained by (or attributed to) the linear relationship between shear strength and precompression stress. 
C)  We expect about 91% of the observed shear strength values to lie on the least squares line. 
D)  We expect to predict the shear strength of a triplet test to within about .91 ton of its true value.

Question 9

Use the linear correlation coefficient given to determine the coefficient of determination ,  
-r = -0.42

Accepted Answer

A)    =-17.64% 
B)    =17.64% 
C)    =-64.81% 
D)    =64.81% 
A)    =-17.64% 
B)    =17.64% 
C)    =-64.81% 
D)    =64.81%

Question 10

Is there a relationship between the raises administrators at State University receive and their performance on the job? A faculty group wants to determine whether job rating (x) is a useful linear predictor of raise (y). Consequently, the group considered the straight-line regression model,   Using the method of least squares, the faculty group obtained the following prediction equation,   Interpret the estimated y-intercept of the line.

Accepted Answer

A)  The base administrator raise at State University is $14,000. 
B)  For a 1-point increase in an administrator's rating, we estimate the administrator's raise to increase $14,000. 
C)  There is no practical interpretation, since rating of 0 is nonsensical and outside the range of the sample data. 
D)  For an administrator who receives a rating of zero, we estimate his or her raise to be $14,000. 
A)  The base administrator raise at State University is $14,000. 
B)  For a 1-point increase in an administrator's rating, we estimate the administrator's raise to increase $14,000. 
C)  There is no practical interpretation, since rating of 0 is nonsensical and outside the range of the sample data. 
D)  For an administrator who receives a rating of zero, we estimate his or her raise to be $14,000.

Question 11

The table shows, for the years 1997-2012, the mean hourly wage for residents of the town of Pity Me and the mean weekly rent paid by the residents.   Summary statistics yield:   = 1222.2771,   = 3031.7125,   = 9144.9375,   = 21.2675, and   Find the least squares line that uses mean hourly wage to predict mean weekly rent. Round values to the nearest ten-thousandth.

Accepted Answer

The answer of The table shows, for the years 1997-2012,...

Question 12

Calculate the linear correlation coefficient for the data below.

Accepted Answer

A)  0.819 
B)  0.990 
C)  0.881 
D)  0.792 
A)  0.819 
B)  0.990 
C)  0.881 
D)  0.792

Question 13

Construct a scatter diagram for the data.
-The data below are the temperatures on randomly chosen days during a summer class and the number of absences on those days.

Accepted Answer

The answer of Construct a scatter diagram for the data.
-The...

Question 14

The following data represent the living situation of newlyweds in a large metropolitan area and their annual household income. What percent of people who make between $35,000 and $50,000 per year own their own home? Round to the nearest tenth of a percent.

Accepted Answer

A)  18.3% 
B)  10.6% 
C)  71.1% 
D)  17.4% 
A)  18.3% 
B)  10.6% 
C)  71.1% 
D)  17.4%

Question 15

The data below are the ages and annual pharmacy b ills (in dollars) of 9 randomly selected employees. Calculate the linear correlation coefficient.

Accepted Answer

A)  0.908 
B)  0.890 
C)  0.960 
D)  0.998 
A)  0.908 
B)  0.890 
C)  0.960 
D)  0.998

Question 16

A large national bank charges local companies for using its services. A bank official reported the results of a regression analysis designed to predict the bank's charges (y), measured in dollars per month, for services rendered to local companies. One independent variable used to predict service charge to a company is the company's sales revenue (x), measured in millions of dollars. Data for 21 companies who use the bank's services were used to fit the model,   The results of the simple linear regression are provided below.   = 2,700 + 20x, s = 65, 2-tailed p-value = 0.064 (for testing   )Interpret the estimate of   , the y-intercept of the line.

Accepted Answer

A)  All companies will be charged at least $2,700 by the bank. 
B)  About 95% of the observed service charges fall within $2,700 of the least squares line. 
C)  There is no practical interpretation since a sales revenue of $0 is a nonsensical value. 
D)  For every $1 million increase in sales revenue, we expect a service charge to increase $2,700. 
A)  All companies will be charged at least $2,700 by the bank. 
B)  About 95% of the observed service charges fall within $2,700 of the least squares line. 
C)  There is no practical interpretation since a sales revenue of $0 is a nonsensical value. 
D)  For every $1 million increase in sales revenue, we expect a service charge to increase $2,700.

Question 17

Make a scatter diagram for the data. Use the scatter diagram to describe how, if at all, the variables are related.
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Accepted Answer

A)  The variables do not appear to be linearly related.   
B)  The variables appear to be positively, linearly related.   
C)  The variables do not appear to be linearly related.   
D)  The variables appear to be negatively, linearly related.   
A)  The variables do not appear to be linearly related.   
B)  The variables appear to be positively, linearly related.   
C)  The variables do not appear to be linearly related.   
D)  The variables appear to be negatively, linearly related.

Question 18

A real estate magazine reported the results of a regression analysis designed to predict the price (y), measured in dollars, of residential properties recently sold in a northern Virginia subdivision. One independent variable used to predict sale price is GLA, gross living area (x), measured in square feet. Data for 157 properties were used to fit the model,   =   +   x. The results of the simple linear regression are provided below.   Interpret the estimate of   , the y-intercept of the line.

Accepted Answer

A)  For every 1-sq ft. increase in GLA, we expect a property's sale price to increase $96,600. 
B)  About 95% of the observed sale prices fall within $96,600 of the least squares line. 
C)  There is no practical interpretation, since a gross living area of 0 is a nonsensical value. 
D)  All residential properties in Virginia will sell for at least $96,600. 
A)  For every 1-sq ft. increase in GLA, we expect a property's sale price to increase $96,600. 
B)  About 95% of the observed sale prices fall within $96,600 of the least squares line. 
C)  There is no practical interpretation, since a gross living area of 0 is a nonsensical value. 
D)  All residential properties in Virginia will sell for at least $96,600.

Question 19

Find the equation of the regression line for the given data. Round values to the nearest thousandth.

Accepted Answer

A)    =2.097x-0.206 
B)    =-0.206x+2.097 
C)    =0.206x-2.097 
D)    =-2.097x+0.206 
A)    =2.097x-0.206 
B)    =-0.206x+2.097 
C)    =0.206x-2.097 
D)    =-2.097x+0.206

Question 20

In a study of feeding behavior, zoologists recorded the number of grunts of a warthog feeding by a lake in the 15 minute period following the addition of food. The data showing the weekly number of grunts and the age of the warthog (in days) are listed below. Find and interpret the value of   . Round   to the nearest thousandth.

Accepted Answer

@#IMG-DLM& =0.627; Approximate

Analyze the residual lot below. Does it violate any of the conditions for an adequate linear model? -

Compute the linear correlation coefficient between the two variables and determine whether a linear relation exists. -

The data below show the age and favorite type of music of 779 randomly selected people. Use What, if any, association exists between favorite music and age? Discuss the association.

Construct a scatter diagram for the data. -The scores of nine members of a local community college women's golf team in two rounds of tournament play are listed below.

Use the linear correlation coefficient given to determine the coefficient of determination , -r = -0.42

Calculate the linear correlation coefficient for the data below.

Construct a scatter diagram for the data. -The data below are the temperatures on randomly chosen days during a summer class and the number of absences on those days.

The following data represent the living situation of newlyweds in a large metropolitan area and their annual household income. What percent of people who make between $35,000 and $50,000 per year own their own home? Round to the nearest tenth of a percent.

The data below are the ages and annual pharmacy b ills (in dollars) of 9 randomly selected employees. Calculate the linear correlation coefficient.

Make a scatter diagram for the data. Use the scatter diagram to describe how, if at all, the variables are related. -

Find the equation of the regression line for the given data. Round values to the nearest thousandth.

Data Collection

Organizing and Summarizing Data

Numerically Summarizing Data

Probability

Discrete Probability Distributions

The Normal Probability Distributions

Sampling Distributions

Estimating the Value of a Parameter Using Confidence Intervals

Hypothesis Tests Regarding a Parameter

Inference on Two Samples

Inference on Categorical Data

Comparing Three or More Means

Inference of the Least-Squares Regression Model

Filters

Exam 4: Describing the Relation Between Two Variables

Analyze the residual lot below. Does it violate any of the conditions for an adequate linear model? -

Compute the linear correlation coefficient between the two variables and determine whether a linear relation exists. -

The data below show the age and favorite type of music of 779 randomly selected people. Use What, if any, association exists between favorite music and age? Discuss the association.

Construct a scatter diagram for the data. -The scores of nine members of a local community college women's golf team in two rounds of tournament play are listed below.

Use the linear correlation coefficient given to determine the coefficient of determination , -r = -0.42

Calculate the linear correlation coefficient for the data below.

Construct a scatter diagram for the data. -The data below are the temperatures on randomly chosen days during a summer class and the number of absences on those days.

The following data represent the living situation of newlyweds in a large metropolitan area and their annual household income. What percent of people who make between $35,000 and $50,000 per year own their own home? Round to the nearest tenth of a percent.

The data below are the ages and annual pharmacy b ills (in dollars) of 9 randomly selected employees. Calculate the linear correlation coefficient.

Make a scatter diagram for the data. Use the scatter diagram to describe how, if at all, the variables are related. -

Find the equation of the regression line for the given data. Round values to the nearest thousandth.

Data Collection

Organizing and Summarizing Data

Numerically Summarizing Data

Probability

Discrete Probability Distributions

The Normal Probability Distributions

Sampling Distributions

Estimating the Value of a Parameter Using Confidence Intervals

Hypothesis Tests Regarding a Parameter

Inference on Two Samples

Inference on Categorical Data

Comparing Three or More Means

Inference of the Least-Squares Regression Model

Filters