The table below displays results from experiments with polygraph instruments. Find the positive predictive value for the test. That is, find the probability that the subject lied, given that the test yields a positive result. Did the Subject Actually Lie? No (Did Not Lie) Yes (Lied) Positive test results 16 41 Negative test results 35 11 The probability is. (Round to three decimal places as needed.)

0.028  0.147  0.321  0.332

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The following table shows the results of a medical test. Positive Test Result Negative Test Result 95.3 4.6 Total 82.6 % 4.6 Has Disease X % 491 24 % 515 Does Not Have Disease 45 Use the preceding data to estimate each of the following. (Express each response as a percentage rounded to one decimal place.) a. If a person has the disease, what is the probability that person tests positive? This is the sensitivity or true positive rate of a test. 214 259 Total b. If a person has the disease, what is the probability that person tests negative? This is sometimes called the false negative rate. 536 238 774 c. If a person does not have the disease, what is the probability that person tests negative? This is the specificity or true negative rate of a test. d. If a person does not have the disease, what is the probability that person tests positive? This is sometimes called the false positive rate. X %

=null O 0.525 O 0.093 O 0.103 QUESTION 3 Find the indicated probability. The table below describes the exercise habits of a group of people suffering from high blood pressure. If one of the 980 subjects is randomly selected, find the probability that the person selected is female given that they exercise occasionally. No Occasional Regular exercise exercise exercise Total Men 361 87 66 514 Women 334 60 72 466 Total 695 147 138 980 Solution: P= 60/147=0.4082 O 0.408 O 0.061 0.15 O 0.129 QUESTION 4 Find the indicated probability.

Refer to the sample data for pre-employment drug screening shown below. If one of the subjects is randomly selected, what is the probability that the test result is a false positive? Who would suffer from a false positive result? Why? Pre-Employment Drug Screening Results Positive test result Negative test result Drug Use Is Indicated Drug Use Is Not Indicated Subject Uses Drugs 42 11 Subject Is Not a Drug User 2 29 The probability of a false positive test result is (Round to three decimal places as needed.) Who would suffer from a false positive result? Why? O A. The person tested would suffer because he or she would be suspected of using drugs when in reality he or she does not use drugs. B. The employer would suffer because the person tested would not be suspected of using drugs when in reality he or she does use drugs. C. The person tested would suffer because he or she would not be suspected of using drugs when in reality he or she does use drugs. D. The employer would suffer…

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5. Suppose a marketing research firm would like to examine if the social networking site that a person primarily uses is influenced by his or her age. In a randomly drawn sample, 337 social network users were asked which site they primarily visited. These data are presented in the following table along with each person's age group. Complete parts a. through c. below. Click the icon to view the data table. a. Using a = 0.025, perform a chi-square test to determine if age group and social networking site used are independent of one another. Identify the null and alternative hypotheses for a chi-square test of independence based on the information in the table. Choose the correct answer below. O A. Ho: Age group and social networking site are independent of one another. H1: The social networking site used affects the age group. O B. Ho: Age group and social networking site are independent of one another. H,: Age group and social networking site are not independent of one another. O C. Ho:…

The following table shows the results of a medical test. Positive Test Result Negative Test Result Total % Has Disease % 165 13 % 178 Does Not Have Disease % 28 97 125 Total Use the preceding data to estimate each of the following. (Express each response as a percentage rounded to one decimal place.) 193 a. If a person tests positive, what is the probability that person has the disease? This is sometimes called the PPV (positive predictive value). 110 303 b. If a person tests positive, what is the probability that person does not have the disease? This is sometimes called the false discovery rate. c. If the person tests negative, what is the probability that person does not have the disease? This is sometimes called the NPV (negative predictive value). d. If the person tests negative, what is the probability that person has the disease? This is sometimes called the false omission rate.

According to a survey in a country, 23% of adults do not have any credit cards. Suppose a simple random sample of 700 adults is obtained. (a) Describe the sampling distribution of p, the sample proportion of adults who do not have a credit card. Choose the phrase that best describes the shape of the sampling distribution of p below. O A. Not normal O B. Approximately normal Determine the mean of the sampling distribution of p. HA = (Round to two decimal places as needed.) Determine the standard deviation of the sampling distribution of p. (Round to three decimal places as needed.) (b) A certain town believes their residents are less likely to own credit cards. They take a random sample of 700 adults in their town. They find a sample proportion of .17. What is the probability of getting 17 or less? The probability is (Round to four decimal places as needed.) Would this be considered unusual?