A pharmaceutical company claims 90% success rate of a newly invented drug to treat arthritis pain. To examine the claim, a doctor administered the prescribed dose to 10 arthritis patients. She observed Y, the number of participants for which the drug was effective. A test is defined so as to reject Ho: p = 0.9 in favour of Ha: p< 0.9 by the rejection region {y
(As per our standard guidelines, we are supposed to answer only 3 sub-parts.)
a) In hypothesis testing, Type I and Type II errors have specific meanings:
Type I Error: In this context, a Type I error would occur if the doctor rejects the null hypothesis p=0.9 (i.e., the drug has a 90% success rate), when in fact it is true. This means that the doctor would conclude that the drug is less effective than claimed when it actually is 90% effective.
Type II Error: A Type II error would occur if the doctor fails to reject the null hypothesis p=0.9, when in fact the alternative hypothesis p < 0.9 is true. In this case, the doctor would conclude that the drug is as effective as claimed (90% success rate), when it is actually less effective.
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