Article Title
DOI
https://doi.org/10.7275/tbfa-x148
Abstract
Applied researchers have employed chi-square tests for more than one hundred years. This paper addresses the question of how one should follow a statistically significant chi-square test result in order to determine the source of that result. Four approaches were evaluated: calculating residuals, comparing cells, ransacking, and partitioning. Data from two recent journal articles were used to illustrate these approaches. A call is made for greater consideration of foundational techniques such as the chi-square tests. Accessed 74,155 times on https://pareonline.net from April 06, 2015 to December 31, 2019. For downloads from January 1, 2020 forward, please click on the PlumX Metrics link to the right.
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Recommended Citation
Sharpe, Donald
(2019)
"Chi-Square Test is Statistically Significant: Now What?,"
Practical Assessment, Research, and Evaluation: Vol. 20, Article 8.
DOI: https://doi.org/10.7275/tbfa-x148
Available at:
https://scholarworks.umass.edu/pare/vol20/iss1/8