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is true? A) The linear model is appropriate. B) The linear model is poor because some residuals are large. C) The linear model is poor because the correlation is near 0 . D) A curved model would be better. E) None of the above. 11. 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 $ \$ 47200 $ 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? 12. Assembly line Your new job at Panasony is to do the final assembly of camcorders. As you learn how, you get faster. The company tells you that you will qualify for a raise if after 13 weeks your assembly time averages under 20 minutes. The data shows your average assembly time during each of your first 10 weeks. a. Which is the explanatory variable? Weeks $ \qquad $ b. What is the correlation between these variables? $ \qquad $ c. You want to predict whether or not you will qualify for that raise. Would it be appropriate to use a linear model? Explain. \begin{tabular}{|c|c|} \hline Week & Time $ (\mathrm{min}) $ \\ \hline 1 & 43 \\ \hline 2 & 39 \\ \hline 3 & 35 \\ \hline 4 & 33 \\ \hline 5 & 32 \\ \hline 6 & 30 \\ \hline 7 & 30 \\ \hline 8 & 28 \\ \hline 9 & 26 \\ \hline 10 & 25 \\ \hline \end{tabular} 8-18 Copyright (8) 2010 Pearson Education, Inc. Publishing as Addison-Wesley.

          is true?
A) The linear model is appropriate.
B) The linear model is poor because some residuals are large.
C) The linear model is poor because the correlation is near 0 .
D) A curved model would be better.
E) None of the above.
11. 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 \( \$ 47200 \) 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?
12. Assembly line Your new job at Panasony is to do the final assembly of camcorders. As you learn how, you get faster. The company tells you that you will qualify for a raise if after 13 weeks your assembly time averages under 20 minutes. The data shows your average assembly time during each of your first 10 weeks.
a. Which is the explanatory variable? Weeks \( \qquad \)
b. What is the correlation between these variables? \( \qquad \)
c. You want to predict whether or not you will qualify for that raise. Would it be appropriate to use a linear model? Explain.
\begin{tabular}{|c|c|}
\hline Week & Time \( (\mathrm{min}) \) \\
\hline 1 & 43 \\
\hline 2 & 39 \\
\hline 3 & 35 \\
\hline 4 & 33 \\
\hline 5 & 32 \\
\hline 6 & 30 \\
\hline 7 & 30 \\
\hline 8 & 28 \\
\hline 9 & 26 \\
\hline 10 & 25 \\
\hline
\end{tabular}
8-18
Copyright (8) 2010 Pearson Education, Inc. Publishing as Addison-Wesley.

is true?
A) The linear model is appropriate.
B) The linear model is poor because some residuals are large.
C) The linear model is poor because the correlation is near 0 .
D) A curved model would be better.
E) None of the above.
11. 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 $ 47200 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?
12. Assembly line Your new job at Panasony is to do the final assembly of camcorders. As you learn how, you get faster. The company tells you that you will qualify for a raise if after 13 weeks your assembly time averages under 20 minutes. The data shows your average assembly time during each of your first 10 weeks.
a. Which is the explanatory variable? Weeks
b. What is the correlation between these variables?
c. You want to predict whether or not you will qualify for that raise. Would it be appropriate to use a linear model? Explain.

Week Time (min)

1 43

2 39

3 35

4 33

5 32

6 30

7 30

8 28

9 26

10 25

8-18
Copyright (8) 2010 Pearson Education, Inc. Publishing as Addison-Wesley.

Added by Mike A.

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