Pg. 470 #6 – Determine whether the samples are independent or dependent. Home Sales Data Set 23 in Appendix B includes the list price and selling price for each of 40 randomly selected homes.

Pg. 471 #11 – Confidence Interval for Cigarette Tar – The mean tar content of a simple random sample of 25 unfiltered king size cigarettes is 21.1mg, with a standard deviation of 3.2mg. The mean tar content of a simple random sample of 25 filtered 100 mm cigarettes is 13.2mg with a standard deviation of 3.7 mg. Construct a 90% confidence interval estimate of the difference between the mean tar content of unfiltered king size cigarettes and the mean tar content of filtered 100 mm cigarettes. Does the result suggest that 100 mm filtered cigarettes have less tar than unfiltered king size cigarettes?

Pg. 471 #16 – Confidence Interval for Supermodels. Use the sample data from Exercise 15 to construct a 98% confidence interval for the difference between the mean height of supermodels and the mean height of women who are not supermodels. What does the result suggest about these two means?

Sample data from Exercise 15 – The heights are measured for the simple random sample of supermodels Crawford, Bundchen, Pestova, Christenson, Hume, Moss, Campbell, Schiffer, and Taylor. They have a mean of 70.0 in and a standard deviation of 1.5 in. Data Set 1 in Appendix B lists the heights of 40 women who are not supermodels, and they have heights with a mean of 63.2 in and a standard deviation of 2.7 in. Use a 0.01 significance level to test the claim that the mean height of supermodels is greater than the mean height of women who are not supermodels.

Pg. 481 #2 – Clinical Test. The drug Dozenol is tested on 40 male subjects recruited from New York and 40 female subjects recruited from California. The researcher pairs the 40 male subjects and the 40 female subjects. Can the methods of this section be used to analyze the results? Why or why not?

This section covers Inferences from Dependent Samples. It uses the P-value method.

Pg. 482 #11 – Are Best Actresses Younger than Best Actors? Listed below are ages of actresses and actors at the times that they won Oscars. The data are paired according to the years that they won. Use a 0.05 significance level to test the common belief that best actresses are younger than best actors. Does the result suggest a problem in our culture?

Best actresses 28 32 27 27 26 24 25 29 41 40 27 42 33 21 35

Best actors 62 41 52 41 34 40 56 41 39 49 48 56 42 62 29

Pg. 508 #1 – Notation. For each of several randomly selected years, the total number of points scored in the Super Bowl football game and the total number of new cars sold in the United States are recorded. For this sample of paired data, what does r represent? What does p represent? Without doing any calculations, estimate the value of r.

Pg, 508 #2 – Correlation and Causality. What is meant by the statement that correlation does not imply causality?

Pg. 508 #4 – Weight Loss and Correlation. In a test of the Weight Watchers weight loss program, weights of 40 subjects are recorded before and after the program. Assume that the before/after weights result in r= 0.876. Is there sufficient evidence to support a claim of a linear correlation between the before/after weights? Does the value of r indicate that the program is effective in reducing weight? Why or why not?

Pg. 509 #10 – Importance of graphing. a) construct a scatter plot. b) find the value of the linear correlation coefficient r, then determine whether there is sufficient evidence to support the claim of a linear correlation between the two variables. c) identify the feature of the data that would be missed if part b was completed without constructing the scatter plot.

x 10 8 13 9 11 14 6 4 12 7 5

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y 7.46 6.77 12.74 7.11 7.81 8.84 6.08 5.39 8.15 6.42 5.73

Pg. 535 #1 – Notation. Assume that you have paired values consisting of heights (in inches) and weights (in lb) from 40 randomly selected men (as in Data Set 1 in Appendix B) and that you plan to use a height of 70 in. to predict weight. In your own words, describe what S e represents.

Pg. 535 #2 - Prediction Interval – Using the heights and weights described in Exercise 1, a height of 70 inches is used to find that the predicted weight is 180 lb. In your own words, describe a prediction interval in this situation.

Pg. 536 #14- Find the a) explained variation b) unexplained variation c) total variation d) coefficient of determination, e) standard error of estimate S e . In each case, there is sufficient evidence to support a claim of a linear correlation so that it is reasonable to use the regression equation when making predictions.

CPI and Subway fare. The Consumer Price Index (CPI) and the cost of subway fare from Table 10-1 in the Chapter Problem are listed below.

CPI 30.2 48.3 112.3 162.2 191.9 197.8

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Subway Fare 0.15 0.35 1.00 1.35 1.50 2.00

Price: $36.71

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