The critical value in a hypothesis test is another name for

The critical value in a hypothesis test:

is another name for the null hypothesis.

is derived from the sample.

is a dissenting view by scientific critics.

is determined by and the type of test.

Solution

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In hypothesis testing, a critical value is a point on the test distribution that is compared to the test statistic to determine whether to reject the null hypothesis. If the absolute value of your test statistic is greater than the critical value, you can declare statistical significance and reject the null hypothesis.

The critical value is determined by finding the value of the known distribution of the test statistic such that the probability of making a Type I error — which is denoted and is called the \"significance level of the test\" — is small (typically 0.01, 0.05, or 0.10).

For example to find critical value for a confidence interval:

Step 1: Subtract the confidence level from 100% to find the level: 100% – 90% = 10%.

Step 2: Convert Step 1 to a decimal: 10% = 0.10.

Step 3: Divide Step 2 by 2 (this is called “/2”).
0.10 = 0.05. This is the area in each tail.

Step 4: Subtract Step 3 from 1 (because we want the area in the middle, not the area in the tail):
1 – 0.05 = .95.

Step 5: Look up the area from Step in the z-table. The area is 1.645. This is your critical value for a confidence level of 90%.