What is the p-value in hypothesis testing?a.The probability of committing a Type 1 errorb.The probability of committing a Type 2 errorc.The probability of observing the test statistic or more extreme values under the assumption that the null hypothesis is trued.The probability of observing the test statistic or more extreme values under the assumption that the alternative hypothesis is true

What is the p-value in hypothesis testing?*1 pointa. The probability of making a Type I errorb. The probability of rejecting the null hypothesis when it's truec. The probability of failing to reject the null hypothesis when it's falsed. The level of significance for the test

The p value is the probability of observing a value of the test statistic as extreme as, or more extreme than, the value actually observed, assuming the alternative hypothesis is trueSelect one:TrueFalse

In the p-value approach to hypothesis testing, how is the p-value used?a.It is compared to the level of significance to determine the rejection region.b.It is used to calculate the effect size of the observed data.c.It represents the probability of committing a Type 1 error.d.It determines the power of the statistical test.

Which of the following is a true statement? a. The larger the p-value, the more evidence there is against the null hypothesis. b. The p-value of a test is the probability of getting a test statistic more extreme than the sample result, given that the null hypothesis is true. c. The p-value of a test is the probability of getting a test statistic more extreme than the sample result, given that the null hypothesis is false. d. If the p-value is less than alpha, then the test statistic value is less than the critical value.

Suppose we want to test the null hypothesis H0 : p = 0.28 against the alternative hypothesis H1 : p ≠ 0.28. Suppose also that we observed 100 successes in a random sample of 400 subjects and the level of significance is 0.05. What is the p-value for this test? Question 2Select one:a.0.05b.0.9563c.0.1802d.0.0901