The less structured (p-value) approach to hypothesis testing is very attractive
ID: 3243707 • Letter: T
Question
The less structured (p-value) approach to hypothesis testing is very attractive when test results are borderline. a type I error is particularly serious. sample size is small. the null hypothesis is false because of a large effect. Two-tailed p-values can be described as being twice as large as the corresponding one-tailed p value. appropriate when the investigator is concerned about deviations in either direction. equivalent shaded areas located in both tails of the sampling distribution. of the above Having committed yourself to a one-tailed test, you must retain the null hypothesis regardless of how far the observed z deviates from the hypothesized population mean in the direction of no concern. the direction of concern. either direction. the negative direction. Power curves cross-classify the likelihood of detecting any possible effect with the level of significance. null hypothesis. decision rule. sample size. Is it's important to detect even a relatively small effect increase the scope of the investigation. sample size. size of the effect. detention regionExplanation / Answer
23) The less structure (p - value) approach to hypothesis testing is very attractive when (a) the results are border lines.
24) Two tailed p - values can be described as being (b) appropriate when the investigator is concerned about deviations in either direction.
25) Having commited ourselves to one tailed test, we must retain the null hypothesis regardless of how far the ofobserved Z - deviates from the hypothesized population mean in (b) the direction of concern.
26) Power curves cross - classify the likelihood of detecting any possible effect with the (d) sample size.
27) If it's important to detect even a relatively small effect, increase (d) retention region.
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