True

Explanation:
In hypothesis testing, a one-sided test (also known as a one-tailed test) evaluates the probability of observing a test statistic as extreme as, or more extreme than, the observed value in one direction (either greater than or less than a certain value). A two-sided test (or two-tailed test), on the other hand, evaluates the probability of observing a test statistic as extreme as, or more extreme than, the observed value in both directions (both greater than and less than a certain value).

Given the same null hypothesis and the same data, the p-value for a one-sided test is half of the p-value for a two-sided test because the two-sided test considers both tails of the distribution, while the one-sided test considers only one tail. Therefore, the probability in one tail is half of the total probability in both tails.

Question

True

Explanation:
In hypothesis testing, a one-sided test (also known as a one-tailed test) evaluates the probability of observing a test statistic as extreme as, or more extreme than, the observed value in one direction (either greater than or less than a certain value). A two-sided test (or two-tailed test), on the other hand, evaluates the probability of observing a test statistic as extreme as, or more extreme than, the observed value in both directions (both greater than and less than a certain value).

Given the same null hypothesis and the same data, the p-value for a one-sided test is half of the p-value for a two-sided test because the two-sided test considers both tails of the distribution, while the one-sided test considers only one tail. Therefore, the probability in one tail is half of the total probability in both tails.

Knowee AI · Accepted Answer

True

Explanation:
In hypothesis testing, a one-sided test (also known as a one-tailed test) evaluates the probability of observing a test statistic as extreme as, or more extreme than, the observed value in one direction (either greater than or less than a certain value). A two-sided test (or two-tailed test), on the other hand, evaluates the probability of observing a test statistic as extreme as, or more extreme than, the observed value in both directions (both greater than and less than a certain value).

Given the same null hypothesis and the same data, the p-value for a one-sided test is half of the p-value for a two-sided test because the two-sided test considers both tails of the distribution, while the one-sided test considers only one tail. Therefore, the probability in one tail is half of the total probability in both tails.

The p-value for a one-sided test is half of the p-value for a two-sided test of the same null hypothesis based on the same data.Answer instructionsTrueFalse

Question

The p-value for a one-sided test is half of the p-value for a two-sided test of the same null hypothesis based on the same data.

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