: Useful for visualizing contingency tables, showing the relative proportion of each combination of categories.
: The table() function generates counts for each category. Analysis of categorical data with R
Descriptive analysis focuses on summarizing frequency and distribution. : Useful for visualizing contingency tables, showing the
Analysis of categorical data in R involves specialized techniques for variables that represent qualitative characteristics, such as gender, region, or recovery status. Unlike continuous numerical data, categorical data—referred to as in R—is divided into discrete groups or "levels". Data Representation and Handling : Useful for visualizing contingency tables
: Use chisq.test() to determine if there is a significant association between two categorical variables.
For more advanced categorical analysis, these packages are widely used:
: Use prop.table() on a frequency table to find proportions. Multiplying by 100 provides percentages.