A paper demonstrated the application of Bayes's Rule for making inferences about testosterone abuse among athletes.In a population of 1000 athletes, suppose 150 are illegally using testosterone. Of the users, suppose 75 would testpositive for testosterone. Of the nonusers, suppose 17 would test positive.a. Given that the athlete is a user, find the probability that a drug test for testosterone will yield a positive result. (Thisprobability represents the sensitivity of the drug test.)(Simplify your answer.)

Here the population of athletes is of strength 1000. Among them 150 are users of testosterone and…

Answered: A paper demonstrated the application of…

Advanced Engineering Mathematics

10th Edition

ISBN:9780470458365

Author:Erwin Kreyszig

Publisher:Erwin Kreyszig

Chapter2: Second-order Linear Odes

Section: Chapter Questions

Problem 1RQ

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2. Suppose that the population parameters for men are m = 85, and for women are m = with b = 9.5 in all cases. 90, a. What is the probability that a 50-year-old man will survive to age 100? b. What is the probability that a 50-year-old woman will survive to age 100? c. Explain in your own words the difference between the survival probabilities for 50-year old men and women.
The probability of randomly sampling a student on campus and finding that they are wearing a red shirt is .3. what is the probability of sampling 10 students and finding that exactly 4 are wearing red shirts in any order? Give your answer as 0.XX
2. All of Dave's customers are neighbors that have yards of about the same size. Dave charges a flat rate of $32 for mowing and trimming and $20 for just mowing. Based on experience, he determines that the probability that a randomly selected customer wants him to mow and trim the lawn is 0.85; the rest of his customers just want him to mow. Let C= the amount Jacob charges a randomly selected customer. (a) Make a table that shows the probability distribution of C. (b) Calculate and interpret the mean of C. (c) Calculate and interpret the standard deviation of C. opp
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I personally have used statistics in trying to challenge the reliability of drug testing results. Suppose the chance of a mistake in the taking and processing of a urine sample for a drug test is just 1 in 100. And your client has a "dirty" (i.e., positive) test result. Only a 1 in 100 chance that it could be wrong? Not necessarily. If the vast majority of all tests given-say 99 in 100-are truly clean, then you get one false dirty and one true dirty in every 100 tests, so that half of the dirty tests are false. Define the following events as: TD = TC = D = event that the person tested is actually dirty C = event that the person tested is actually clean (a) Using the information in the quote, find the values of each of the following. event that the test result is dirty event that the test result is clean (i) P(TD|D) (ii) P(TDIC) (iii) P(C) (iv) P(D) X X (b) Use the law of total probability to find P(TD). (c) Use Bayes' rule to evaluate P(C|TD). X
An Insurance company study shows that 70% of the auto insurance claims submitted for property damage were submitted by males user 25 years of age. Suppose 6 property damage claims involving automobiles are selected at random. Let X be the number of claims (among 6 the selected) that are made by males under age 25. Question 1 Find the probability that all 6 claims are made by males under age 25.
A gender-selection technique is designed to increase the likelihood that a baby will be a girl. In the results of the gender-selection technique, 948948 births consisted of 492492 baby girls and 456456 baby boys. In analyzing these results, assume that boys and girls are equally likely. a. Find the probability of getting exactly 492492 girls in 948948 births. b. Find the probability of getting 492492 or more girls in 948948 births. If boys and girls are equally likely, is 492492 girls in 948948 births unusually high?
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Please help me determine what the probability was that it was a boy is
The 2006 Statistical Abstract of the United States reports on a survey that asked a national sample of 80,000 American households about pet ownership. Suppose (for now) that one-third of all American households own a pet cat. Still supposing that one-third of all American households own a pet cat, between what two values do you expect 95% of all sample proportions to fall?
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refer to the above question 1. if a student is selected at random then the probability that he/she has passed only one test (either math or state, bot not both) is

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