An article in the Journal of Statistics Education reported the price of diamonds of different sizes in Singapore dollars (SGD). The following table contains a data set that is consistent with this data, adjusted to US dollars in 2004: $\begin{array}{l} \begin{array} { | c | c | } \hline \text { 2004 US \$ } & \text { Carat } \\ \hline 494.82 & 0.12 \\ \hline 768.03 & 0.17 \\ \hline 1105.03 & 0.20 \\ \hline 1508.88 & 0.25 \\ \hline 1826.18 & 0.28 \\ \hline 2096.89 & 0.33 \\ \hline \end{array}\quad \begin{array} { | c | c | } \hline \text { 2004 US \$ } & \text { Carat } \\ \hline 688.24 & 0.15 \\ \hline 944.90 & 0.18 \\ \hline 1071.75 & 0.21 \\ \hline 1504.44 & 0.26 \\ \hline 1908.28 & 0.29 \\ \hline 2409.76 & 0.35 \\ \hline \end{array}\quad \begin{array} { | c | c | } \hline \text { 2004 US S } & \text { Carat } \\ \hline 748.10 & 0.16 \\ \hline 1076.18 & 0.19 \\ \hline 1289.20 & 0.23 \\ \hline 1597.63 & 0.27 \\ \hline 2038.09 & 0.32 \\ \hline & \\ \hline \end{array} \end{array}$ -Make a scatterplot and describe the association between the size of the diamond (carat) and the cost (in US dollars).

@#IMG-DLM& There is a strong, positive,

Exam 2: Data | Examlex

Earning power A college's job placement office collected data about students' GPAs and the salaries they earned in their first jobs after graduation. The mean GPA was 2.9 with a standard deviation of 0.4. Starting salaries had a mean of $47,200 with a SD of $8500. The correlation between the two variables was r = 0.72. The association appeared to be linear in the scatterplot. (Show work.) a. Write an equation of the model that can predict salary based on GPA. b. Do you think these predictions will be reliable? Explain. c. Your brother just graduated from that college with a GPA of 3.30. He tells you that based on this model the residual for his pay is -$1880. What salary is he earning?

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Question 81

The bigger the stop sign, the more expensive it is. Here is a graph of the height of a sign in inches versus its cost in dollars. $The bigger the stop sign, the more expensive it is. Here is a graph of the height of a sign in inches versus its cost in dollars. To achieve linearity, the data was transformed using a square root function of cost. Here are the results and a residual plot. Dependent Variable: sqrt(cost) \mathrm{R} (correlation coefficient) =0.98946627 R-s q=0.97904349 s: 0.2141 \begin{array}{lrr} \text { Parameter } & \text { coeff } & \text { se } \\ \text { Intercept } & 1.1857 & 0.4346 \\ \text { height } & 0.1792 & 0.0151 \end{array} -Do you think this transformation for linearity was successful? Why?$ To achieve linearity, the data was transformed using a square root function of cost. Here are the results and a residual plot. Dependent Variable: sqrt(cost) $\mathrm{R}$ (correlation coefficient) $=0.98946627$ $R-s q=0.97904349$ s: 0.2141 Parameter coeff se Intercept 1.1857 0.4346 height 0.1792 0.0151 $The bigger the stop sign, the more expensive it is. Here is a graph of the height of a sign in inches versus its cost in dollars. To achieve linearity, the data was transformed using a square root function of cost. Here are the results and a residual plot. Dependent Variable: sqrt(cost) \mathrm{R} (correlation coefficient) =0.98946627 R-s q=0.97904349 s: 0.2141 \begin{array}{lrr} \text { Parameter } & \text { coeff } & \text { se } \\ \text { Intercept } & 1.1857 & 0.4346 \\ \text { height } & 0.1792 & 0.0151 \end{array} -Do you think this transformation for linearity was successful? Why?$ -Do you think this transformation for linearity was successful? Why?

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Question 82

For families who live in apartments the correlation between the family's income and the amount of rent they pay is r = 0.60. Which is true? I. In general, families with higher incomes pay more in rent. II. On average, families spend 60% of their income on rent. III. The regression line passes through 60% of the (income$, rent$) data points.

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Question 83

In an effort to decide if there is an association between the year of a postal increase and the new postal rate for first class mail, the data were gathered from the United States Postal Service. In 1981, the United States Postal Service changed their rates on March 22 and November 1. This information is shown in the table below. Year Rate 1971 0.08 1974 0.10 1975 0.13 1978 0.15 1981 0.18 1981 0.20 1985 0.22 1988 0.25 1991 0.29 1995 0.32 -Create a model to predict postal rates from the year.

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Question 84

An article in the Journal of Statistics Education reported the price of diamonds of different sizes in Singapore dollars (SGD). The following table contains a data set that is consistent with this data, adjusted to US dollars in 2004: 2004 US S Carat 494.82 0.12 768.03 0.17 1105.03 0.20 1508.88 0.25 1826.18 0.28 2096.89 0.33 2004 US \ Carat 688.24 0.15 944.90 0.18 1071.75 0.21 1504.44 0.26 1908.28 0.29 2409.76 0.35 2004 US S Carat 748.10 0.16 1076.18 0.19 1289.20 0.23 1597.63 0.27 2038.09 0.32 -Create a model to predict diamond costs from the size of the diamond.

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Question 85

R-sq is a measure of ……

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Question 86

When using midterm exam scores to predict a student's final grade in a class, the student would prefer to have a

(Multiple Choice)

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Question 87

Suppose we collect data hoping to be able to estimate the prices of commonly owned new cars (in $) from their lengths (in feet). Of these possibilities, the slope of the line of best fit is most likely to Be

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Question 88

An article in the Journal of Statistics Education reported the price of diamonds of different sizes in Singapore dollars (SGD). The following table contains a data set that is consistent with this data, adjusted to US dollars in 2004: 2004 US \ Carat 494.82 0.12 768.03 0.17 1105.03 0.20 1508.88 0.25 1826.18 0.28 2096.89 0.33 2004 US \ Carat 688.24 0.15 944.90 0.18 1071.75 0.21 1504.44 0.26 1908.28 0.29 2409.76 0.35 2004 US S Carat 748.10 0.16 1076.18 0.19 1289.20 0.23 1597.63 0.27 2038.09 0.32 -Make a scatterplot and describe the association between the size of the diamond (carat) and the cost (in US dollars).

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Question 89

We can use the length of a man's hand span to predict his height, with a correlation coefficient of r = 0.60. If we change our measurements from cm to m, the new correlation will be

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Question 90

If you have a puppy who you are feeding Hill's Science Diet® original puppy food, the feeding guidelines for puppies who are 10 to 12 months old are as follows (Source: Hill's feeding guidelines): Weight (lbs) 2 5 8 10 20 40 60 80 100 120 Food (cups) 1/3 2/3 2 1-1/8 2 3-1/4 4-1/3 5.5 6.5 7-1/3 A scatterplot of the data is: $If you have a puppy who you are feeding Hill's Science Diet® original puppy food, the feeding guidelines for puppies who are 10 to 12 months old are as follows (Source: Hill's feeding guidelines): \begin{array}{l|cccccccccc} \text {Weight (lbs) }& 2 & 5 & 8 & 10 & 20 & 40 & 60 & 80 & 100 & 120 \\ \hline\text { Food (cups)} & 1 / 3 & 2 / 3 & 2 & 1-1 / 8 & 2 & 3-1 / 4& 4-1 / 3 & 5.5 & 6.5 & 7-1 / 3 \end{array} A scatterplot of the data is: Does it seem reasonable to perform a linear regression to predict amount of food from the puppy's weight based on this data set? Explain.$ Does it seem reasonable to perform a linear regression to predict amount of food from the puppy's weight based on this data set? Explain.

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Question 91

A residuals plot is useful because I. it will help us to see whether our model is appropriate. II. it might show a pattern in the data that was hard to see in the original scatterplot. III. it will clearly identify influential points.

(Multiple Choice)

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Question 92

An article in the Journal of Statistics Education reported the price of diamonds of different sizes in Singapore dollars (SGD). The following table contains a data set that is consistent with this data, adjusted to US dollars in 2004: 2004 US S Carat 494.82 0.12 768.03 0.17 1105.03 0.20 1508.88 0.25 1826.18 0.28 2096.89 0.33 2004 US S Carat 688.24 0.15 944.90 0.18 1071.75 0.21 1504.44 0.26 1908.28 0.29 2409.76 0.35 2004 US S Carat 748.10 0.16 1076.18 0.19 1289.20 0.23 1597.63 0.27 2038.09 0.32 -Would it be better for a customer buying a diamond to have a negative residual or a positive residual from this model? Explain.

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Question 93

Subaru costs Data collected from internet ads for 1999 Subarus were used to create a model to estimate the asking price of the car based on the number of miles it had been driven. The model has $\hat{r}$ =0.47 and equation $\hat{\text{ Price}}$ = 15,327 - 0.11(Miles). The plot of residuals versus the predicted price is shown. $Subaru costs Data collected from internet ads for 1999 Subarus were used to create a model to estimate the asking price of the car based on the number of miles it had been driven. The model has \hat{r} =0.47 and equation \hat{\text{ Price}} = 15,327 - 0.11(Miles). The plot of residuals versus the predicted price is shown. a. Do you think you could make accurate estimates of Subaru prices with this model? Explain. b. Interpret the slope of the line. c. One of the cars in the data set had been driven 42,000 miles. How much was the owner asking for it? (Show work.)$ a. Do you think you could make accurate estimates of Subaru prices with this model? Explain. b. Interpret the slope of the line. c. One of the cars in the data set had been driven 42,000 miles. How much was the owner asking for it? (Show work.)

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Question 94

Baseball coaches use a radar gun to measure the speed of pitcher’s fastball. They also record outcomes such as hits and strikeouts. The scatterplot below shows the relationship between the average speed of a fastball and the average number of strikeouts per nine innings for each pitcher on the Bulldogs, based on the past season. -Do you think a model based on these data could accurately predict the average number of strikeouts for a pitcher with an average fastball speed of 70 mph.? Explain.

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Question 95

A company's sales increase by the same amount each year. This growth is...

(Multiple Choice)

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Question 96

If a data set has a relationship that is best described by a linear model, than the residual plot will

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Question 97

Match each graph with the appropriate correlation coefficient. _ 0.98 _ _ 0.73 0.09 _-0.99

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Question 98

Two variables that are actually not related to each other may nonetheless have a very high correlation because they both result from some other, possibly hidden, factor. This is an example of

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Question 99

Personal debt According to The World Almanac and Book of Facts 2004, the debt per capita for the years 1990-2001 gives the following scatterplot: $Personal debt According to The World Almanac and Book of Facts 2004, the debt per capita for the years 1990-2001 gives the following scatterplot: Regression output gives the equation of the regression line as \hat{\text{ Debt }} =-2,231,226+1128 (Year) with R^{2}=98.8 \% . a. What is the response variable? b. What is the correlation coefficient r? c. Explain in context what the slope of the line means. d. Explain in context what R^{2}=98.8 \% means. e. You decide to take a look at a residuals plot before making any predictions. Based on the following residuals plot, does linear regression seem appropriate for these data? Explain.$ Regression output gives the equation of the regression line as $\hat{\text{ Debt }}$ $=-2,231,226+1128$ (Year) with $R^{2}=98.8 \%$ . a. What is the response variable? b. What is the correlation coefficient r? c. Explain in context what the slope of the line means. d. Explain in context what $R^{2}=98.8 \%$ means. e. You decide to take a look at a residuals plot before making any predictions. Based on the following residuals plot, does linear regression seem appropriate for these data? Explain. $Personal debt According to The World Almanac and Book of Facts 2004, the debt per capita for the years 1990-2001 gives the following scatterplot: Regression output gives the equation of the regression line as \hat{\text{ Debt }} =-2,231,226+1128 (Year) with R^{2}=98.8 \% . a. What is the response variable? b. What is the correlation coefficient r? c. Explain in context what the slope of the line means. d. Explain in context what R^{2}=98.8 \% means. e. You decide to take a look at a residuals plot before making any predictions. Based on the following residuals plot, does linear regression seem appropriate for these data? Explain.$

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Question 100

Showing 81 - 100 of 150

R-sq is a measure of ……

When using midterm exam scores to predict a student's final grade in a class, the student would prefer to have a

Suppose we collect data hoping to be able to estimate the prices of commonly owned new cars (in $) from their lengths (in feet). Of these possibilities, the slope of the line of best fit is most likely to Be

We can use the length of a man's hand span to predict his height, with a correlation coefficient of r = 0.60. If we change our measurements from cm to m, the new correlation will be

A residuals plot is useful because I. it will help us to see whether our model is appropriate. II. it might show a pattern in the data that was hard to see in the original scatterplot. III. it will clearly identify influential points.

A company's sales increase by the same amount each year. This growth is...

If a data set has a relationship that is best described by a linear model, than the residual plot will

Match each graph with the appropriate correlation coefficient. _ 0.98 _ _ 0.73 0.09 _-0.99

Two variables that are actually not related to each other may nonetheless have a very high correlation because they both result from some other, possibly hidden, factor. This is an example of

Stats Start Here

Displaying and Describing Categorical Data

Displaying and Comparing Qualitative Data

Understanding and Comparing Distributions

The Standard Deviation As a Ruler and the Normal Model

Scatterplots, Association, and Correlation

Filters

Exam 2: Data

R-sq is a measure of ……

When using midterm exam scores to predict a student's final grade in a class, the student would prefer to have a

Suppose we collect data hoping to be able to estimate the prices of commonly owned new cars (in $) from their lengths (in feet). Of these possibilities, the slope of the line of best fit is most likely to Be

We can use the length of a man's hand span to predict his height, with a correlation coefficient of r = 0.60. If we change our measurements from cm to m, the new correlation will be

A residuals plot is useful because I. it will help us to see whether our model is appropriate. II. it might show a pattern in the data that was hard to see in the original scatterplot. III. it will clearly identify influential points.

A company's sales increase by the same amount each year. This growth is...

If a data set has a relationship that is best described by a linear model, than the residual plot will

Match each graph with the appropriate correlation coefficient. _ 0.98 _ _ 0.73 ______ 0.09 _______-0.99

Two variables that are actually not related to each other may nonetheless have a very high correlation because they both result from some other, possibly hidden, factor. This is an example of

Stats Start Here

Displaying and Describing Categorical Data

Displaying and Comparing Qualitative Data

Understanding and Comparing Distributions

The Standard Deviation As a Ruler and the Normal Model

Scatterplots, Association, and Correlation

Filters

Match each graph with the appropriate correlation coefficient. _ 0.98 _ _ 0.73 0.09 _-0.99