- Title
- Exploring how to simply approximate the P-value of a chi-squared statistic
- Creator
- Beh, Eric J.
- Relation
- Austrian Journal of Statistics Vol. 47, Issue 3, p. 63-75
- Publisher Link
- http://dx.doi.org/10.17713/ajs.v47i3.757
- Publisher
- Austrian Society of Statistics
- Resource Type
- journal article
- Date
- 2018
- Description
- Calculating the p-value of any test statistic is of paramount importance to all statistically minded researchers across all areas of study. Many, these days, take for granted how the p-value is calculated and yet it is a pivotal quantity in all forms of statistical analysis. For the study of 2×2 tables where dichotomous variables are assessed for association, the chi-squared statistic, and its p-value, are fundamental quantities to all analysts, especially those in the health and allied disciplines. Examining the association between dichotomous variables is easily achieved through a very simple formula for the chi-squared statistic and yet the p-value of this statistic requires far more computational effort. This paper proposes and explores a very simple approximation of the p-value for a chi-squared statistic given its degrees of freedom. After providing a review of a variety of common ways for determining the quantile of the chi-squared distribution given the level of significance and degrees of freedom, we shall derive an approximation based on the classic quantile formula given in 1977 by D. C. Hoaglin. We examine this approximation using a simple 2×2 contingency table example then show that it is extremely precise for all chi-squared values ranging from 0 to 50.
- Subject
- chi-squared statistic; Fisher's approximation; Hoaglin's approximation; p-value approximation; Wilson and Hilferty's approximation
- Identifier
- http://hdl.handle.net/1959.13/1402994
- Identifier
- uon:35088
- Identifier
- ISSN:1026-597X
- Rights
- The Austrian Journal of Statistics publish open access articles under the terms of the Creative Commons Attribution (CC BY) License. The Creative Commons Attribution License (CC-BY) allows users to copy, distribute and transmit an article, adapt the article and make commercial use of the article. The CC BY license permits commercial and non-commercial re-use of an open access article, as long as the author is properly attributed. Copyright on any research article published by the Austrian Journal of Statistics is retained by the author(s). Authors grant the Austrian Journal of Statistics a license to publish the article and identify itself as the original publisher. Authors also grant any third party the right to use the article freely as long as its original authors, citation details and publisher are identified.
- Language
- eng
- Full Text
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