Pearson-Fisher Chi-Square Statistic Revisited

Information

Sorana D. Bolboacă¹  Lorentz Jäntschi²  Adriana F. Sestraş²  Radu E. Sestraş² 

[1] “Iuliu Haţieganu” University of Medicine and Pharmacy Cluj-Napoca, 6 Louis Pasteur, Cluj-Napoca 400349, Romania; E-Mail:;University of Agricultural Sciences and Veterinary Medicine Cluj-Napoca, 3-5 Mănăştur, Cluj-Napoca 400372, Romania; E-Mails:

关键词: Chi-square statistics;    Fisher exact test;    Chi-square distribution;    2 × 2 contingency table;   

DOI  :  10.3390/info2030528

来源: mdpi

【 摘 要 】

The Chi-Square test (χ² test) is a family of tests based on a series of assumptions and is frequently used in the statistical analysis of experimental data. The aim of our paper was to present solutions to common problems when applying the Chi-square tests for testing goodness-of-fit, homogeneity and independence. The main characteristics of these three tests are presented along with various problems related to their application. The main problems identified in the application of the goodness-of-fit test were as follows: defining the frequency classes, calculating the X² statistic, and applying the χ² test. Several solutions were identified, presented and analyzed. Three different equations were identified as being able to determine the contribution of each factor on three hypothesizes (minimization of variance, minimization of square coefficient of variation and minimization of X² statistic) in the application of the Chi-square test of homogeneity. The best solution was directly related to the distribution of the experimental error. The Fisher exact test proved to be the “golden test” in analyzing the independence while the Yates and Mantel-Haenszel corrections could be applied as alternative tests.

【 授权许可】

CC BY   
© 2011 by the authors; licensee MDPI, Basel, Switzerland.