
December 4th, 2008, 04:58 AM
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 | Flow Master | | Join Date: Dec 2007 Location: Zeitgeist
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Quote:
Originally Posted by oxyron I have the following problem:
"When a thread-cutting machine is operating properly, only 2% of the units produced are defective. Since the machine was bumped by a forklift, the quality-control manager is concerned that it may require expensive downtime and readjustment. The manager wishes to test, null hypothesis H0: P =< 0.02 against H1: P > 0.02. Using a random sample of 400 units, his decision rule for the test is defined as: Reject H0 if P-hat > 0.034; and don't reject H0 if P-hat =< 0.034."
a) Find probability of Type I error (alpha) when P = 0.02
b) Find probability of Type II error (beta) and the power, when P = 0.04
c) Find power of test when the true proportion P = 0.05
My issue is, we just started this material (what H0 and H1 is, and the two types of errors) and have not covered this yet. Mr F says: Then wouldn't it be better then to wait until it has been covered ....?
So, I went to the book to gain a clue. I assume since P is =< 0.02, we will want to use a right tail/upper tail test. However, I'm not sure if we use Z or t, and really, where I go from here to answer a b and c.
Please help? | (0.034)(400) = 13.6.
a) Calculate Pr(X > 13 | X ~ Binomial(p = 0.02, n = 400)).
b) Calculate Pr(X < 14 | X ~ Binomial(p = 0.04, n = 400)).
Power  .
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