Categorical Hypotheses

Categorical hypotheses are used to test if different categories of data vary significantly from each other. This type of hypothesis is common in scenarios where you want to examine if distinct groups have different proportions or frequencies concerning a characteristic. For instance, if you want to test whether gender affects vegetarianism rates, you would categorize participants as male or female and compare the proportions of vegetarians in each group.

To test a categorical hypothesis properly, methods like the Chi-squared test are often used. This requires ensuring the data is unbiased, independent, and identically distributed. A common rule suggests that each category or cell in a contingency table should have at least five observations to achieve reliable results. However, when dealing with small sample sizes, one must be cautious as minor changes in data can significantly impact the test's outcome 1 .