482 CHAPTER 9 Correlation and Regression Graphical Analysis In Exercises 15–18, the scatter plots show the results of a survey of 20 randomly selected adults ages 24 –35. Using age as the explanatory variable, match each graph with the appropriate description. Explain your reasoning. (a) Age and body temperature (b) Age and balance on student loans (c) Age and income (d) Age and height 15. 26 30 20 40 60 80 100 34 x Age In thousands of units y 16. 26 30 60 65 70 75 80 34 x Age In units y 17. 26 30 10 20 30 40 50 34 x Age In thousands of units y 18. 26 30 70 80 90 100 110 34 x Age In units y In Exercises 19–22, two variables are given that have been shown to have correlation but no cause-and-effect relationship. Describe at least one possible reason for the correlation. 19. Value of home and life span 20. Alcohol use and tobacco use 21. Ice cream sales and homicide rates 22. Marriage rate in Kentucky and number of deaths caused by falling out of a fishing boat Using and Interpreting Concepts Constructing a Scatter Plot and Determining Correlation In Exercises 23–28, (a) display the data in a scatter plot, (b) calculate the sample correlation coefficient r, (c) describe the type of correlation, if any, and interpret the correlation in the context of the data, and (d) use Table 11 in Appendix B to make a conclusion about the correlation coefficient. If convenient, use technology. Let a = 0.01. 23. Age and Vocabulary The ages (in years) of 11 children and the numbers of words in their vocabulary Age, x 1234 5 63524 6 Vocabulary size, y 3 220 540 1100 2100 2600 730 2200 260 1200 2500 24. Height and IQ The heights (in inches) of 8 high school students and their scores on an IQ test Height, x 62 58 65 67 59 64 65 57 IQ score, y 109 102 107 114 96 110 116 128
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