Reason for Using Frequency and Percentage to Analyse Categorical Data

Abstract

Data analysis enables researchers to organise information and communicate findings clearly. Categorical data are commonly collected in surveys and other descriptive studies becauseresponses can be grouped into distinct categories. Frequency and percentage are two simplemeasures commonly used to summarise such data. Frequency shows the number of observationsin a category, while percentage shows the proportion of the total represented by that category.This article examines the reasons for using frequency and percentage to analyse categorical data.It discusses their meaning, their usefulness in describing distributions, their value in comparinggroups, and their role in presenting research findings. It also considers the use of a 50%benchmark for interpreting response percentages, as identified in the material supplied for this assignment. The discussion draws on Kaur, Stoltzfus, and Yellapu (2018), Aliyu (2023), and Reierson Draugalis and Plaza (2009), among other academic sources. The article concludes that frequency and percentage are clear and practical descriptive measures for categorical data when they are calculated and interpreted correctly.