In hypothesis testing, does choosing between the critical value method or the p-value method affect your conclusion? explain. choose the correct answer below. a. yes, because the critical value method uses critical value(s) to identify the rejection region(s). the p-value method compares the p-value with the level of significance alphaα. b. no, because both methods involve comparing the standardized test statistic with the rejection region(s). c. yes, because the p-value method is more accurate than the critical value method. d. yes, because the critical value method is more accurate than the p-value method. e. no, because both involve comparing the test statistic's probability with the level of significance.

A.

Step-by-step explanation:

Yes, because the critical value method uses critical value(s) to identify the rejection region(s). The P-value method compares the P-value with the level of significance alpha.

Explanation:  When you reduce your significance value, the critical value either gets smaller, or larger depending on the tails.  This means that your test statistic would also have to get smaller or larger depending on the tail in order to reject the null hypothesis.

At test that rejected the null hypothesis at 5% may not reject it at 1%

the figures below are made out of circles, semicircles, quarter … find the area and the perimeter of each figure and give your answers as a completely simplified exact value in terms of π (no approximations). remember that we'll also have to cut whatever areas we get in half, since we're only dealing

step-by-step explanation:

idk

step-by-step explanation:

use that smart brain