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10. A report of a clinical trial of a new drug •for herpes simplex II versus a placebo noted that
the new drug gave a higher proportion of success than the placebo. The report ended with
the statement: chi-sq = 4.72; p <0.05. In light of this information, we may conclude that

(A) fewer than one in 20 will fail to benefit from the drug
(B) the chance that an individual patient will fail to benefit is less than 0.05
(C) if the drug were effective, the probability of the reported finding is less than one in 20
(D) if the drug were ineffective, the probability of the reported finding is less than 0.05
(E) the null hypothesis is false

please explain


Hopefully this isn’t too late:
The answer is D

I reviewed another post to confirm; the way answers c & d are written is really confusing (and I love this stuff).  This is a very poorly written/framed question.

A and B have the word …benefit" in it.
P < 0.05 is statistically significant but that does NOT mean there’s clinical significance or clinical benefit, patient benefit, individual benefit.

E is confusing.
One reason I’m not selecting it as an answer:
In general, we either (1) reject the null hypothesis or (2) fail to reject the null hypothesis.
Second/third reasons I’m not selecting it as an answer:  do we really know if the computational p-value (the computed results) are more than or less than 0.05 AND, it’s too easy, given choices c & d.

The prob that the drug is ineffective is 0.05, or alpha.
Why:  5% of the time, researchers rejected the null (H0) (therefore, accepting the alternative/research hypothesis, H1) when in reality, the null should have been rejected (therefore, NOT accepting H1).

final thoughts

The thing I see missing in all study materials is that H1 is the thing researches want to see happen.  To get to H1, H0 must be rejected.  There’s a little more to this.

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