Analysis Of Categorical Data With R May 2026

: Use chisq.test() to determine if there is a significant association between two categorical variables.

: Use prop.table() on a frequency table to find proportions. Multiplying by 100 provides percentages. Analysis of categorical data with R

For more advanced categorical analysis, these packages are widely used: : Use chisq

In R, categorical data is stored using the factor class. While string variables can be treated as text, converting them to factors ensures they are correctly interpreted in statistical models. For more advanced categorical analysis, these packages are

: Useful for visualizing contingency tables, showing the relative proportion of each combination of categories.

Inferential methods allow researchers to test hypotheses about categorical relationships in a population.

: For binary outcomes (e.g., "Success/Failure"), the glm() function with family = binomial is the standard for modeling how predictors influence the probability of an outcome.