Many consumer groups feet that the Country A drug approval process is too easy a

Question

Many consumer groups feet that the Country A drug approval process is too easy and as a result, too many drug are approved that are later found to be unsafe. On the other hand, a number of industry loobyists have pushed for a more lenient approval process so that pharmaceutical companies can get new drugs approval more easily and quickly. Consider a null hypothesis that a new, unapproved drug is unsafe and an alternative hypothesis that a new, unapproved drug is safe. Complete parts (a) through (d) below b. Which type error are the consumer groups trying to avoid? Explain. Choose the correct answer below. A. The consumer groups are trying to avoid a Type II error because they think that too many safe drugs are unapproved. B. The consumer groups are trying to avoid a Type I error because they think that too many safe drugs are unapproved. C. The consumer groups are trying to avoid a Type I error because they think that too many unsafe drugs are unapproved. D. The consumer groups are trying to avoid a Type II error because they think that too many unsafe drugs are unapproved. c. Which type he industry lobbyists trying to avoid? Explain. Choose the correct answer below. A. The industry lobbyists are trying to avoid a Type II error because they think that the process of approving safe drugs is hard B. The industry lobbyists are trying to avoid a Type I error because they think that the process of approving sate drugs hard C. The industry lobbyists are trying to avoid a Type II error because they think that the process of approving safe drugs is too easy D. The industry lobbyists are trying to avoid a Type I error because they think that the process of approving safe drugs is too easy d. How could it be possible to lower the chances of both Type I and type II errors? Choose the correct answer below. A. Lower the value of beta B. Lower the value of alpha. C. Increase the value of alpha. D. Increase the sample size.

Explanation / Answer

In statistical hypothesis testing, a type I error is the incorrect rejection of a true null hypothesis (a "false positive"), while a type II error is incorrectly retaining a false null hypothesis (a "false negative").

b)

Option C is correct.

c)

Option A is correct.

d)

Lower the value of alpha.

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