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

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

If the p-value is less than 0.05 then  we would only see a sample as extreme as the one that we saw less than 5% of the time Correct Answer  assuming that the null hypothesis is true, we would only see a sample as extreme as the one that we saw less than 5% of the time   there is more than a 5% chance that the null hypothesis is true   there is less than a 5% chance that the null hypothesis is true.

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.

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.