Menu Close

What is the rejection region and why is it important?

What is the rejection region and why is it important?

A critical region, also known as the rejection region, is a set of values for the test statistic for which the null hypothesis is rejected. i.e. if the observed test statistic is in the critical region then we reject the null hypothesis and accept the alternative hypothesis.

What is difference between acceptance and rejection region?

The subset that is considered to be consistent with the null hypothesis is called the “acceptance region”; another subset is called the “rejection region” (or “critical region”). If the sample outcome falls into the rejection region, then the null hypothesis is rejected (i.e. the alternative hypothesis is accepted).

What does the rejection region depend on?

What Does the Rejection Region Depend on? The area that is cut-off actually depends on the significance level. Say the level of significance, α, is 0.05. Then we have α divided by 2, or 0.025 on the left side and 0.025 on the right side.

Why the rejection region is important?

If the value falls in the rejection region, it means you have statistically significant results; You can reject the null hypothesis. If the p-value falls outside the rejection region, it means your results aren’t enough to throw out the null hypothesis.

How do you use rejection region?

Rejection Regions and Alpha Levels You, as a researcher, choose the alpha level you are willing to accept. For example, if you wanted to be 95% confident that your results are significant, you would choose a 5% alpha level (100% – 95%). That 5% level is the rejection region.

What does a 5% level of significance mean?

0.05
The significance level, also denoted as alpha or α, is the probability of rejecting the null hypothesis when it is true. For example, a significance level of 0.05 indicates a 5% risk of concluding that a difference exists when there is no actual difference.

Which Alpha level is most difficult to reject the null hypothesis?

0.05 to 0.01
Decreasing alpha from 0.05 to 0.01 increases the chance of a Type II error (makes it harder to reject the null hypothesis).

What is the region of non rejection?

(2) Definition: The nonrejection region is the set, or range, of values of the test statistic for which the null hypothesis H0 is not rejected, or retained.

How do you know to reject or fail to reject?

After you perform a hypothesis test, there are only two possible outcomes.

  1. When your p-value is less than or equal to your significance level, you reject the null hypothesis. The data favors the alternative hypothesis.
  2. When your p-value is greater than your significance level, you fail to reject the null hypothesis.

Which is the best definition of rejection region?

rejection region. noun Statistics. the set of values of a test statistic for which the null hypothesis is rejected.

What is a rejection region in a null hypothesis?

What is a Rejection Region? A rejection region (a.k.a. critical region) in a Null Hypothesis Statistical Test is a part of the parameter space such that observing a result that falls under it will lead to the rejection of a the null hypothesis.

Is the rejection region on the right side of the curve?

The shaded region or the critical region is equal to the significance level (α). The next figure again shows the rejection region for the one-tailed test and how the critical value appears on it: Here the curve shows that it is a right-tailed test, so the rejection region appears on the right side of the curve.

Where is the rejection region on the Z-table?

Using the same significance level, this time, the whole rejection region is on the left. So, the rejection region has an area of α. Looking at the z-table, that corresponds to a Z -score of 1.645.