Statistical Methods

Unit 4 - Testing of hypotheses

4.4.Level of significance
In testing a given hypothesis, the maximum probability with which we would be willing to risk type I error is called the level of significance of the tests, denoted by α.
In other words, it is a way of quantifying the amount of risk one wants to take in rejecting a true hypothesis.

Usually 5% or 1% levels of significance are chosen. These levels, however, depend on the gravity of the risk which costs in decision making.

To illustrate suppose 5% level of significance is chosen in designing a test of hypothesis, then there are about 5 chances in 100 that the hypothesis is rejected when it should be accepted, i.e. one is 95% confident about the right decision. The decision as to which values go into the rejection region and acceptance region is made on the basis of desired level of significance ‘α’. Tests of hypothesis are sometimes called tests of significance because of the term level of significance and the computed value of the test statistic that falls in the rejection region is said to be significant.