Concept explainers
Does It Make Sense? For Exercises 5–8, determine whether the statement makes sense (or is clearly true) or does not make sense (or is clearly false). Explain clearly; not all of these statements have definitive answers, so your explanation is more important than your chosen answer.
7. Smoking and Cotinine. Data showed a strong
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Statistical Reasoning for Everyday Life (5th Edition)
- Heart rate during laughter. Laughter is often called “the best medicine,” since studies have shown that laughter can reduce muscle tension and increase oxygenation of the blood. In the International Journal of Obesity (Jan. 2007), researchers at Vanderbilt University investigated the physiological changes that accompany laughter. Ninety subjects (18–34 years old) watched film clips designed to evoke laughter. During the laughing period, the researchers measured the heart rate (beats per minute) of each subject, with the following summary results: Mean = 73.5, Standard Deviation = 6. n=90 (we can treat this as a large sample and use z) It is well known that the mean resting heart rate of adults is 71 beats per minute. Based on the research on laughter and heart rate, we would expect subjects to have a higher heart beat rate while laughing.Construct 95% Confidence interval using z value. What is the lower bound of CI? a) Calculate the value of the test statistic.(z*) b) If…arrow_forwardA researcher believes that the so-called “sugar high” is not real. He gathered 30 adolescents and recorded their activity level in the scale of 0 – 100 (0 = not active and 100 = super active). First, he recorded participants’ activity level before they consumed candy. After recording their pre-sugar activity level, the researcher gave out 5 Snickers bars to participants. Then, he recorded their post-sugar activity level. The average difference between post-sugar and pre-sugar activity level is 50 (i.e., the activity levels are higher after sugar than prior to it) with a standard deviation of 10. A). Complete test statistic and critical values B). Conclusionarrow_forwardA researcher believes that the so-called “sugar high” is not real. He gathered 30 adolescents and recorded their activity level in the scale of 0 – 100 (0 = not active and 100 = super active). First, he recorded participants’ activity level before they consumed candy. After recording their pre-sugar activity level, the researcher gave out 5 Snickers bars to participants. Then, he recorded their post-sugar activity level. The average difference between post-sugar and pre-sugar activity level is 50 (i.e., the activity levels are higher after sugar than prior to it) with a standard deviation of 10. A). What is the type of test you will use? (z-test, single-sample t-test, paired-samples t-test, or independent samples t-test) and why (what information provided in the problem)B). What are the hypotheses (Be Specific)arrow_forward
- Large companies typically collect volumes of data before designing a product, not only to gain information as to whether the product should be released, but also to pinpoint which markets would be the best targets for the product. Several months ago, I was interviewed by such a company while shopping at a mall. I was asked about my exercise habits and whether or not I'd be interested in buying a video/DVD designed to teach stretching exercises. I fall into the male, 18 – 35-years-old category, and I guessed that, like me, many males in that category would not be interested in a stretching video. My friend Amanda falls in the female, older-than-35 category, and I was thinking that she might like the stretching video. After being interviewed, I looked at the interviewer's results. Of the 97 people in my market category who had been interviewed, 16 said they would buy the product, and of the 101 people in Amanda's market category, 31 said they would buy it. Assuming that these data came…arrow_forwardLarge companies typically collect volumes of data before designing a product, not only to gain information as to whether the product should be released, but also to pinpoint which markets would be the best targets for the product. Several months ago, I was interviewed by such a company while shopping at a mall. I was asked about my exercise habits and whether or not I'd be interested in buying a video/DVD designed to teach stretching exercises. I fall into the male, 18 – 35-years-old category, and I guessed that, like me, many males in that category would not be interested in a stretching video. My friend Diane falls in the female, older-than-35 category, and I was thinking that she might like the stretching video. After being interviewed, I looked at the interviewer's results. Of the 93 people in my market category who had been interviewed, 17 said they would buy the product, and of the 113 people in Diane's market category, 34 said they would buy it. Assuming that these data came…arrow_forwardA researcher tests whether cocaine use increases impulsive behavior, which is measured as the number of impulsive events per hour. The researcher gives either 0 ng, 10 ng, 15 ng, or 20 ng to each group of mice. 1. What is the independent and dependent variable?arrow_forward
- Critical Thinking. For Exercises 5–20, watch out for these little buggers. Each of these exercises involves some feature that is somewhat tricky. Find the (a) mean, (b) median, (c) mode, (d) midrange, and then answer the given question. Football Player Numbers Listed below are the jersey numbers of 11 players randomly selected from the roster of the Seattle Seahawks when they won Super Bowl XLVIII. What do the results tell us?arrow_forwardD. P(pass/morning) = 0.28 P(pass/afternoon) = 0.53 Conclussion: A student taking the test in the morning has a greater chance of passing it than a student taking it in the afternoon.arrow_forwardLevene's test tests whetherarrow_forward
- A researcher wanted to determine if using an octane booster would increase gasoline mileage. A random sample of seven cars was selected; the cars were driven for two weeks without the booster and two weeks with the booster. Use the definitions of X, and X, as given in the table. Consequently, D= X, -X,. 1 Gasoline Mileage Without booster, X, Gasoline Mileage Without booster,X, (mpg) (mpg) 21.2 23.8 25.4 25.6 20.9 22.4 28.3 27.6 22.8 24.5 28.8 27.3 25.2 23.4 State the alternative hypothesis.arrow_forwardAn education researcher claims that 62% of college students work year-round. In a random sample of 300 college students, 186 say they work year-round. At a=0.01, is there enough evidence to reject the researcher's claim? Complete parts (a) through (e) below. (a) Identify the claim and state H0 and Ha. Identify the claim in this scenario. Select the correct choice below and fill in the answer box to complete your choice. (Type an integer or a decimal. Do not round.) A. The percentage of college students who work year-round is not ______%. B. At most ______% of college students workyear-round. C. At least ______% of college students work year-round. D. ______% of college students work year-round. (b) Find the critical value(s) and identify the rejection region(s). (c) Find the standardized test statistic z. (d) Decide whether to reject or fail to reject the null hypothesis and (e) interpret the decision in the context of the original claim.arrow_forwardA certain affects virus 0.4% of the population (in a population of 100,000 people, 400 will be infected with the virus). A test used to detect the virus in a person is positive 87% of the time if the person has the virus (true positive) and it is positive 14% of the time if the person does not have the virus (false positive). Fill in the remainder of the following table and use it to answer the questions below. Infected Not Infected Total Positive Test Negative Test Total 400 99,600 100,000 Round all percents to the nearest tenth of a percent as needed. a) Examine the "Positive Test" row of the table. If a person tests positive for the virus, what is the probability that the person is really infected. (Note: in medical terminology, this probability measures the "positive predictive value" of the test) b) If a person tests negative for the virus, what is the probability that the person really is not infected. (This is called the "negative predictive value")arrow_forward
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