1 point for the form of the rms error 1 point for the

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1 point for the form of the RMS error, 1 point for the numeric value, 1 point for the sum- marizing sentence including units. No work shown (even with a correct numeric answer) earns no points.
(e) (3 points) Another researcher (Pat) comments that Sam is looking at data for both men and women, when it is well known that those two groups have very different metabolisms and eating practices, and thus should be examined separately. Sam is skeptical, but looking at a color-coded scatterplot, does see two distinct gender groups. Given that the correlation for both groups together is 0.64, should Sam expect the correlations within each gender group to be greater than 0.64, less than 0.64, or about 0.64? Why? Please give both the statistical term and a short explanation .
Stat 20 Midterm Exam, Page 8 of 14 11 March 2014 1 point for the correct choice, 1 point for the term “attenuation”, 1 point for a complete explanation.
Stat 20 Midterm Exam, Page 9 of 14 11 March 2014 4. A t-shirt company is interested in the relationship between the number of people working in their factory on a given day and the number of t-shirts produced. One year of data is examined and the following summary statistics are found. Number of Employees: mean = 150 people sd = 10 people Number of t-shirts produced: mean = 10,000 t-shirts sd = 150 t-shirts correlation: r = 0.8 (a) (4 points) Assuming the scatterplot of production vs number of workers is football shaped, find the 80 th percentile for the number of t-shirts produced. Show your work and write a sentence to summarize, including units.
(b) (4 points) The factory manager notices that there are 179 workers on a certain day. The manager uses the data shown here and calculates that the factory should produce about 10,348 t-shirts, give or take 90 t-shirts on that day. Given this information, on what percentage of days when the manager has 179 employees, should the manager expect to produce more than 10,555 t-shirts? (You can safely assume that the manager’s calculations are correct.)

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