417 Where You’re Going In this chapter, you will continue your study of inferential statistics and hypothesis testing. Now, however, instead of testing a hypothesis about a single population, you will learn how to test a hypothesis that compares two populations. For instance, in the yoga study, a random sample of people who do not use yoga was also surveyed. Here are the study’s findings for this second group. Where You’ve Been In Chapter 6, you were introduced to inferential statistics and you learned how to form a confidence interval to estimate a population parameter. Then, in Chapter 7, you learned how to test a claim about a population parameter, basing your decision on sample statistics and their sampling distributions. Using data from the National Health Interview Survey, a study was conducted to analyze the characteristics of people who use yoga and people who do not use yoga. The study was published in the Journal of General Internal Medicine. Some of the results are shown below for a random sample of people who use yoga. People Who Do Not Use Yoga 1n = 29,9482 Characteristic Frequency Proportion 40 to 49 years old 6,290 0.2100 From the western region of the United States 5,691 0.1900 Non-smoking 23,360 0.7800 People Who Use Yoga 1n = 15932 Characteristic Frequency Proportion 40 to 49 years old 367 0.2304 From the western region of the United States 415 0.2605 Non-smoking 1323 0.8305 From these two samples, can you conclude that there is a difference in the proportion of 40- to 49-year-olds, people from the western region of the United States, or non-smokers between people who use yoga and people who do not use yoga? Or, might the differences in the proportions be due to chance? In this chapter, you will learn to answer these questions by testing the hypothesis that the two proportions are equal. For instance, for non-smokers, you can conclude, at the 1% level of significance, that the proportion of people who use yoga is different from the proportion of people who do not use yoga.
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