Reason for Using Frequency and Percentage to Analyse Categorical Data

The type of data collected in a study should guide the statistical method used to analyze it. Categorical data classify observations into groups or categories rather than measuring them on a continuous numerical scale. For this reason, frequency and percentage are commonly used to describe categorical data. Frequency indicates how many observations fall into a category, while percentage shows the proportion of the total represented by that category. Kaur et al. (2018) discuss frequency and percentage as useful descriptive statistics, and Bulanov et al. (2021) explain that qualitative variables are usually presented with absolute values and percentages. Studies across different fields also demonstrate the practical use of these measures in analyzing questionnaires and demographic data (Enebeli et al., 2024; Makinde & Yabagi, 2024; Pereira et al., 2024). This article explains why frequency and percentage are suitable for categorical data, particularly for showing distributions, comparing categories, identifying common responses, and presenting results in a form that is easy to understand. It also notes that frequency and percentage are mainly descriptive and may need to be followed by inferential tests when a study seeks to test relationships or differences.