A42 TRY IT YOURSELF ANSWERS Chapter 9 Section 9.1 1. 5 1015202530 2 4 6 8 10 12 14 16 x y Years out of school Annual contribution (in thousands of dollars) It appears that there is a negative linear correlation. As the number of years out of school increases, the annual contribution tends to decrease. 2. 62 66 70 74 78 60 70 80 90 100 110 x Height (in inches) Pulse rate (in beats per minute) y It appears that there is no linear correlation between height and pulse rate. 3. x Salary (in millions of dollars) Average attendance y 50 100 150 200 250 300 10,000 20,000 30,000 40,000 50,000 60,000 It appears that there is a positive linear correlation. As the team salary increases, the average attendance per home game tends to increase. 4. -0.908. Because r is close to -1, this suggests a strong negative linear correlation. As the number of years out of school increases, the annual contribution tends to decrease. 5. 0.792. Because r is close to 1, this suggests a strong positive linear correlation. As the team salaries increase, the average attendance per home game tends to increase. 6. 0 r0 ≈ 0.908 7 0.875. The correlation is significant. There is enough evidence at the 1% level of significance to conclude that there is a significant linear correlation between the number of years out of school and the annual contribution. 7. There is enough evidence at the 1% level of significance to conclude that there is a significant linear correlation between the salaries and average attendances per home game for the teams in Major League Baseball. Section 9.2 1. ny = -0.380x + 12.876 2. ny = 152.932x + 7811.244 3. (1) 58.645 minutes (2) 75.120 minutes Section 9.3 1. 0.958. About 95.8% of the variation in the times is explained. About 4.2% of the variation is unexplained. 2. 6.218 3. 411.225 6 y 6 1179.381 You can be 95% confident that when the gross domestic product is $4 trillion, the carbon dioxide emissions will be between 411.225 and 1179.381 million metric tons. Section 9.4 1. ny = 46.385 + 0.540x 1 - 4.897x2 2. (1) 90 (2) 74 (3) 81 Chapter 10 Section 10.1 1. Tax preparation method % of people Expected frequency Accountant 24% 120 By hand 20% 100 Computer software 35% 175 Friend or family 6% 30 Tax preparation service 15% 75 2. There is not enough evidence at the 5% level of significance to support the sociologist’s claim that the age distribution differs from the age distribution 10 years ago. 3. There is enough evidence at the 5% level of significance to reject the claim that the distribution of different-colored candies in bags of peanut M&M’s is uniform. Section 10.2 1. E1, 1 ≈ 426.549, E1, 2 ≈ 75.451, E1, 3 ≈ 271.120, E1, 4 ≈ 195.669, E1, 5 ≈ 35.210, E2, 1 ≈ 421.451, E2, 2 ≈ 74.549, E2, 3 ≈ 267.880, E2, 4 ≈ 193.331, E2, 5 ≈ 34.790 2. There is enough evidence at the 1% level of significance to conclude that student’s living arrangement depends on borrowing status. 3. There is enough evidence at the 1% level of significance to conclude that whether or not a tax credit would influence an adult to make a charitable donation is dependent on age.
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