Chapter 8: Q85E (page 452)
Question: Find the following probabilities for the standard normal random variable z:
Short Answer
Answer
A random variable is a mathematical expression of a statistical study's result.
Chapter 8: Q85E (page 452)
Question: Find the following probabilities for the standard normal random variable z:
Answer
A random variable is a mathematical expression of a statistical study's result.
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Get started for freeQuestion: Is caffeine addictive? Does the caffeine in coffee, tea, and cola induce an addiction similar to that induced by alcohol, tobacco, heroin, and cocaine? In an attempt to answer this question, researchers at Johns Hopkins University examined 27 caffeine drinkers and found 25 who displayed some type of withdrawal symptoms when abstaining from caffeine. [Note: The 27 caffeine drinkers volunteered for the study.] Furthermore, of 11 caffeine drinkers who were diagnosed as caffeine dependent, 8 displayed dramatic withdrawal symptoms (including impairment in normal functioning) when they consumed a caffeine-free diet in a controlled setting. The National Coffee Association claimed, however, that the study group was too small to draw conclusions. Is the sample large enough to estimate the true proportion of caffeine drinkers who are caffeine dependent to within .05 of the true value with 99% confidence? Explain.
What are the treatments for a designed experiment with two factors, one qualitative with two levels (A and B) and one quantitative with five levels (50, 60, 70, 80, and 90)?
Assume that . Calculate the pooled estimator for each of the following cases:
a.
b.
c.
d.
Note that the pooled estimate is a weighted average of the sample variances. To which of the variances does the pooled estimate fall nearer in each of the above cases?
Product failure behavior. An article in Hotwire (December 2002) discussed the length of time till the failure of a product produced at Hewlett Packard. At the end of the product’s lifetime, the time till failure is modeled using an exponential distribution with a mean of 500 thousand hours. In reliability jargon, this is known as the “wear-out” distribution for the product. During its normal (useful) life, assume the product’s time till failure is uniformly distributed over the range of 100 thousand to 1 million hours.
a. At the end of the product’s lifetime, find the probability that the product fails before 700 thousand hours.
b. During its normal (useful) life, find the probability that the product fails before 700 thousand hours.
c. Show that the probability of the product failing before 830 thousand hours is approximately the same for both the normal (useful) life distribution and the wear-out distribution.
Suppose you want to estimate the difference between two population means correct to within 1.8 with a 95% confidence interval. If prior information suggests that the population variances are approximately equal to and you want to select independent random samples of equal size from the populations, how large should the sample sizes , and , be?
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