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How is the critical region utilized in hypothesis testing?
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.
When can a null hypothesis be rejected?
Usually when the test statistic is in the critical region.
How do you know if you have enough information to draw an hypothesis test in statistics?
You can test a hypothesis with very little information. For hypothesis testing you will have a null hypothesis, and alternative and some test statistic. The hypothesis test consists of checking whether or not the test statistic lies in the critical region. If it does, then you reject the null hypothesis and accept the alternative. The default option is to stick with the null hypothesis.If the number of observations is very small then the critical region is so small that you have virtually no chance of rejecting the null: you will default to accepting it.Different test have different powers and these depend on the underlying distribution of the variable being tested as well as the sample size.
How critical value is calculated in Kolmogorov-Smirnov test?
if my data followed to a special distribution, how can i calculate the critical value of k-s test in this case?
What is z critical value for lower tailed test for 5 percent?
1.64
