rue or false, and explain: (a) The p-value of a test equals its observed signicance level. (b) The alternative hypothesis is another way of explaining the results; it says the difference is due to chance.
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" The p-value is the probability of observing a test statistic at least as extreme as the one observed, assuming the null hypothesis is true. The observed significance level is the smallest level of significance at which we would have rejected the null hypothesis. Show more…
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True or false, and explain: (a) The $P$ -value of a test equals its observed significance level. (b) The alternative hypothesis is another way of explaining the results; it says the difference is due to chance.
True or false: The advantage of a p-value vs. a t-statistic approach to hypothesis testing is that it allows for selecting the significance level to determine whether the null hypothesis should be rejected. Explain your answer
Adi S.
The p-value of a sample is the probability of seeing a sample with: a. at most as much evidence in favor of the alternative hypothesis as the sample actually observed. b. at most as much evidence in favor of the null hypothesis as the sample actually observed. c. at least as much evidence in favor of the null hypothesis as the sample actually observed. d. at least as much evidence in favor of the alternative hypothesis as the sample actually observed.
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