9 Review Exercises 516 CHAPTER 9 Correlation and Regression Section 9.1 In Exercises 1–4, (a) display the data in a scatter plot, (b) calculate the sample correlation coefficient r, and (c) describe the type of correlation and interpret the correlation in the context of the data. 1. The numbers of pass attempts and passing yards for seven professional quarterbacks for a recent regular season (Source: National Football League) Pass attempts, x 626 595 608 492 390 443 368 Passing yards, y 4581 4336 3803 3733 2942 2933 2657 2. The numbers of wildland fires (in thousands) and wildland acres burned (in millions) in the United States for eight years (Source: National Interagency Fire Center) Fires, x 47.6 63.3 68.2 67.7 71.5 58.1 50.5 59.0 Acres, y 4.3 3.6 10.1 5.5 10.0 8.8 4.7 10.1 3. The intelligence quotient (IQ) scores and brain sizes (in grams) for nine adults (Source: Cerebral Cortex) IQ score, x 89 95 107 120 73 108 92 80 127 Brain size, y 1400 1485 1570 1550 1446 1210 1620 1710 1570 4. The annual per capita sugar consumptions (in kilograms) and the average numbers of cavities of 11- and 12-year-old children in seven countries Sugar consumption, x 2.1 5.0 6.3 6.5 7.7 8.7 11.6 Cavities, y 0.59 1.51 1.55 1.70 2.18 2.10 2.73 In Exercises 5–8, use Table 11 in Appendix B, or perform a hypothesis test using Table 5 in Appendix B to make a conclusion about the correlation coefficient. 5. Refer to the data in Exercise 1. At a = 0.05, is there enough evidence to conclude that there is a significant linear correlation between the data? (Use the value of r found in Exercise 1.) 6. Refer to the data in Exercise 2. At a = 0.05, is there enough evidence to conclude that there is a significant linear correlation between the data? (Use the value of r found in Exercise 2.) 7. Refer to the data in Exercise 3. At a = 0.01, is there enough evidence to conclude that there is a significant linear correlation between the data? (Use the value of r found in Exercise 3.) 8. Refer to the data in Exercise 4. At a = 0.01, is there enough evidence to conclude that there is a significant linear correlation between the data? (Use the value of r found in Exercise 4.)
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