American Board of Surgery Qualifying Exam (ABS QE) Practice Test

The Chi-square test is suitable for which type of data?

1. Continuous data

2. Ordinal data

3. Nominal, un-ordered categories

4. Skewed data

The correct answer is: Nominal, un-ordered categories

The Chi-square test is designed to analyze categorical data, specifically nominal data, which consists of un-ordered categories. This statistical test evaluates whether there is a significant association between two categorical variables or if the observed frequencies differ from expected frequencies under a specific hypothesis. For instance, if researchers want to determine if there's a relationship between gender and preference for a particular product (with responses grouped into categories like "likes," "dislikes," and "neutral"), the Chi-square test helps assess whether any apparent differences in preferences across genders are statistically significant. In contrast, continuous data involves measurements that can take on any value within a range and are analyzed using different statistical methods. Ordinal data, while it includes categories, is ranked and may not meet the assumptions for the Chi-square test since the test does not utilize the order of the categories in its calculations. Skewed data refers to the distribution of continuous data and also falls outside the scope of what the Chi-square test addresses. Thus, the suitability of the Chi-square test is clearly limited to nominal, un-ordered categories, making it the appropriate choice.