What is Level of Significance?

One of the major parameters in hypothesis testing is the level of significance (denoted as the symbol α) that defines the threshold of rejecting the null hypothesis in favour of the alternative hypothesis. The level of significance represents the maximum probability of the Type I error, that is, the error of incorrectly rejecting, despite the truth of the null hypothesis.

In hypothesis testing, researchers before running the data analysis, go through the process of specifying a significance level. So the present level is an index of the assessing evidence against the null hypothesis. Frequently applied alpha values with p < 0.10, p < 0.01 or. p < 0.05, which may change as the specifics of the study provide a reason. Otherwise, researchers may set other values to find the ratio between errors of the to-type1 and type 2.

Level of Significance Symbol

The letter α (alpha) is used as the symbol to show the significance level in statistics. This is the main indicator of the accuracy of the results. This symbol annually serves as the basis of determining how to apply statistical significance.

Level of Significance-Definition, Steps and Examples

Level of significance or Statistical significance is an important terminology used in Statistics. Level of significance is the measurement of the statistical significance. The level of significance explains whether the null hypothesis is accepted or rejected. In this article, we are going to discuss the level of significance in detail.

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