Chi-Square Contingency Table Analysis

9 Pages Posted: 21 Oct 2008

See all articles by Phillip E. Pfeifer

Phillip E. Pfeifer

University of Virginia - Darden School of Business

Abstract

This technical note describes the chi-square statistic as applied to independence tests using contingency table data. The independence test checks to see if two (or more) categorical variables are independent. This is the same thing as checking to see if the rows share a common set of column probabilities (and vice versa).

Excerpt

UVA-QA-0694

Rev. Apr. 27, 2011

Chi-Square Contingency Table Analysis

This note describes the chi-square statistic as applied to the analysis of contingency tables. Contingency tables (also known as cross-tabs) are tables reporting the observed counts (frequencies) of cases classified according to two (or more) categorical variables. The chi-square test checks to see if the relative frequency along one variable changes depending on the classification based on the other. In other words, it tests for a correlation or association between two (or more) categorical variables. While not the most sophisticated test, the chi-square test is easy to implement.

In-Store Music and Product Choice

Over a two-week period, researchers played stereotypical French and stereotypical German music on alternating days behind a supermarket display featuring a carefully matched selection of four French and four German wines. The resulting numbers of bottles sold are reported in Table 1. Tables of this type are called cross-tabs because the 82 cases (observations) are tabulated not just by kind of wine or kind of music, but by the combination of the two. This table is also called a contingency table because it reflects the degree to which the mix of wine sold is contingent on the type of music played.

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Keywords: data analysis, management science, marketing research, statistics

Suggested Citation

Pfeifer, Phillip E., Chi-Square Contingency Table Analysis. Darden Case No. UVA-QA-0694, Available at SSRN: https://ssrn.com/abstract=1284267

Phillip E. Pfeifer (Contact Author)

University of Virginia - Darden School of Business ( email )

P.O. Box 6550
Charlottesville, VA 22906-6550
United States
434-924-4803 (Phone)

HOME PAGE: http://www.darden.virginia.edu/faculty/Pfeifer.htm

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