Tutorial 6:Level of significance and power of the test

The probability of making a Type I error is called level of significance (α). Normally researchers would aim to minimize the probability of making a Type I error. Most researchers will set this probability to 0.05.

The probability of making a Type II error is (β). The power of the study is calculated from (1-β) and is defined as the probability of detecting a real difference when the null hypothesis is false.

These parameters have to be predetermined by the researcher prior to the study to avert the risk of erroneously accepting the null hypothesis (even though it is really false)

Once the hypothesis, level of significance and power of the study have been fixed, the researcher can proceed to determine the statistical processes for the proper conduct and analysis of the study.

Tutorial-5:Statistical Hypothesis

After identifying and defining the variable the researcher has to develop the hypothesis about his study if his study is an experimental study. An experimental study has two hypotheses one is null hypothesis, which is a statement of no effect or no association and the alternative hypothesis is a statement, which depicts the researcher’s interests.
Two types of errors can occur while making conclusions regarding the null hypothesis: Type I error and Type II error. A Type I error refers to rejecting the null hypothesis when the null hypothesis is true (false positive). A Type II error refers to accepting the null hypothesis when it is false (false negative).