Introduction to Statistical Tests of Significance

Open Access

Year : 2023 | Volume :10 | Issue : 2 | Page : 8-13
By

    Noohi Khan

  1. Assistant Professor II, Amity School of Applied Sciences, Amity University, Lucknow, Uttar Pradesh, India

Abstract

Hypothesis examination is the process in which we compare between two differing hypotheses. i.e. the null hypothesis H0 and the alternative hypothesis. As the null hypothesis is examined, a choice is either correct or incorrect. An incorrect conclusion can be produced in two methods: We can deny the null hypothesis once it is true (Type I error) or we cannot succeed to eliminate the null hypothesis when it is incorrect (Type II error). The possibility of getting Type I and Type II errors is defined by leading and beta edition, individually. The p-estimate is the possibility of getting findings as excessive as the examined outcomes of a statistical hypothesis test, assuming that null assumption is appropriate. A reduced p-value means that there is stronger evidence in preference of the alternate hypothesis.

Keywords: Alternative, hypothesis, level of significances, non-parametric, null, P-value, parametric

[This article belongs to Research & Reviews : Journal of Statistics(rrjs)]

How to cite this article: Noohi Khan , Introduction to Statistical Tests of Significance rrjs 2023; 10:8-13
How to cite this URL: Noohi Khan , Introduction to Statistical Tests of Significance rrjs 2023 {cited 2023 Jun 21};10:8-13. Available from: https://journals.stmjournals.com/rrjs/article=2023/view=92406

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Regular Issue Open Access Article
Volume 10
Issue 2
Received May 12, 2021
Accepted June 21, 2021
Published June 21, 2023