Best Answer

A test statistic is a value calculated from a set of observations.

A critical value depends on a null hypothesis about the distribution of the variable and the degree of certainty required from the test. Given a null hypothesis it may be possible to calculate the distribution of the test statistic. Then, given an alternative hypothesis, it is may be possible to calculate the probability of the test statistic taking the observed (or more extreme) value under the null hypothesis and the alternative. Finally, you need the degree of certainty required from the test and this will determine the value such that if the test statistic is more extreme than the critical value, it is unlikely that the observations are consistent with the hypothesis so it must be rejected in favour of the alternative hypothesis.

It may not always be possible to calculate the distribution function for the variable.

Q: What is the difference between a test statistic and a critical value?

Write your answer...

Submit

Still have questions?

Continue Learning about Math & Arithmetic

When you formulate and test a statistical hypothesis, you compute a test statistic (a numerical value using a formula depending on the test). If the test statistic falls in the critical region, it leads us to reject our hypothesis. If it does not fall in the critical region, we do not reject our hypothesis. The critical region is a numerical interval.

search

The critical value is an FINISHED

Any decision based on the test statistic is marginal in such a case. It is important to remember that the test statistic is derived on the basis of the null hypothesis and does not make use of the distribution under the alternative hypothesis.

error

Related questions

Normally you would find the critical value when given the p value and the test statistic.

The critical value is used to test a null hypothesis against an alternative hypothesis at some pre-defined level of significance. A test statistic is calculated from the outcomes of a set of trials and if this test statistic is more extreme than the critical value then the null hypothesis must be rejected in favour of the alternative.

Every possible experimental outcome results in a value of the test statistic. The non-critical region is the collection of test statistic values that are associated with acceptance of the null hypothesis.

Not enough information - nature of step progression towards critical value has to be specified (sample size, linear vs. logarithmic vs. whatever, etc.).

When you formulate and test a statistical hypothesis, you compute a test statistic (a numerical value using a formula depending on the test). If the test statistic falls in the critical region, it leads us to reject our hypothesis. If it does not fall in the critical region, we do not reject our hypothesis. The critical region is a numerical interval.

the DIFFERENCE between the place value and the face value is 991

The difference between the Actual Value & Earned Value is the Project Cost Variance

search

Surplus value is the difference between the value that workers produce and what they are paid in wages.

the same as the difference between ct and k

The critical value is an FINISHED

Any decision based on the test statistic is marginal in such a case. It is important to remember that the test statistic is derived on the basis of the null hypothesis and does not make use of the distribution under the alternative hypothesis.