The p-value in hypothesis testing represents which of the following: Group of answer choicesThe probability of failing to reject the null hypothesis, given the observed resultsThe probability that the null hypothesis is true, given the observed resultsThe probability that the observed results are statistically significant, given that the null hypothesis is trueThe probability of observing results as extreme or more extreme than currently observed, given that the null 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.

In a hypothesis test, the p-value is 0.009. The stated significance level is 0.05. What is the decision regarding the null hypothesis? a. More information is needed to make a decision. b. Not reject the null hypothesis c. Reject the null hypothesis. d. Reject the alternative hypothesis.

When the p-value is used for hypothesis testing , the null hypothesis is rejected if Group of answer choicesp value is less than or equal to alphapvalue is greater than alphap value is equal to alphaalpha less than the pvalue