Reason for using Frequence and percentage to Analyse Categorical Data

Data analysis is an important stage of research because it transforms raw responses into meaningful information for decision-making. Frequency and percentage are two simple descriptive techniques that are particularly suitable for categorical data. Frequency shows the number of observations in each category, while percentage shows the proportion of the total represented by each category. We would be discussing the reasons for using frequency and percentage to analyse categorical data, using Zaron Cosmetics Limited as an organisational example. To also explains the use of a 50% benchmark when interpreting responses obtained from non-Likert and Likert-scale questions. And shows that these techniques are easy to understand, facilitate comparison, reveal patterns and present research findings clearly. The 50% benchmark can be used as a descriptive rule for identifying whether a majority of respondents selected a particular response, provided that the researcher clearly justifies its use. However, it should not be confused with statistical significance.