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Inferential statistics allows researchers to examine whether there is enough evidence in favor or against the claims about a sample that is drawn from a population. The statistical process used for supporting or rejecting claims on the basis of sample data is referred to as significance testing. This entry starts with the explanation of the concepts central to significance testing such as null and alternative hypothesis, and one-directional and two-directional tests. Second, this entry describes what statistical significance means and the steps researchers should follow in the process of significance testing. Finally, this entry outlines statistical errors unique to significance testing.

Null and Alternative Hypothesis

In order to conduct a significance test, researchers first state predictions about the population as a null and alternative hypothesis. The starting ...

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