Research Topic · Peer-Reviewed

Chi Square Tests

A Chi Square Test is a statistical test used to determine if there is a significant difference between the expected frequencies and the observed frequencies in one or more categories. It is used to analyze categorical data and assess the likelihood of a relationship between two variables. The Chi Square Test is an i…

Curated from this journal's research 📚 12 peer-reviewed articles cited Cited 5× across the literature 🔖 ISSN 2643-2811 🗓 Reviewed June 2026

Overview

A Chi Square Test is a statistical test used to determine if there is a significant difference between the expected frequencies and the observed frequencies in one or more categories. It is used to analyze categorical data and assess the likelihood of a relationship between two variables. The Chi Square Test is an important tool for scientists and researchers because it helps identify meaningful relationships in data. It also allows researchers to draw informative conclusions on the relationship between variables. The Chi Square Test can also be used to check for significant differences between groups, such as in studies that compare the effectiveness of treatments.

Research published in this journal

12 peer-reviewed articles, ranked by relevance. Each links to its DOI.

How this research is being cited

The 12 articles above have been cited 5 times in the scholarly literature. Citation data via OpenAlex and Crossref, updated Jun 2026.

A sample of recent works citing this journal's research on Chi Square Tests, linking to each citing work.

Editorial oversight

Curated from peer-reviewed research published in Model Based Research (ISSN 2643-2811).

Journal editorial board
Yoshiaki Kikuchi · Japan Yung-Yao Chen · Taiwan Yang Chen · United States

This page summarises published research for orientation; it is not medical or professional advice.