Analysis | Of Categorical Data With R

: By default, R orders levels alphabetically. For ordinal data (e.g., "Low", "Medium", "High"), you can define a specific order using the levels argument in factor() or functions in the forcats package . Descriptive Statistics

: Cross-tabulating two or more variables can be done with table() or the crosstab() function from the descr package . Data Visualization Analysis of categorical data with R

: Use prop.table() on a frequency table to find proportions. Multiplying by 100 provides percentages. : By default, R orders levels alphabetically

: Display changes or flows between categorical variables over time using the ggalluvial package . Inferential Statistics and Modeling Data Visualization : Use prop

: Provides functions for multivariate categorical data analysis using the Akaike Information Criterion (AIC). Categorical Data Descriptive Statistics

Descriptive analysis focuses on summarizing frequency and distribution.

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