Reason for Using Frequency and Percentage to Analyse Data Regardless of the Degree and Reason for Using Benchmark of 50% to Analyse Data Collected from both Non-Likert and Likert Scale Regardless of the Degree

Abstract

This article examines the rationale behind using frequency and percentage as primary analytical tools for categorical data in descriptive research. The discussion establishes that categorical data, being nominal in nature, necessitates analytical approaches distinct from those used for continuous or interval data. Frequency and percentage distributions provide intuitive, accessible, and meaningful summaries of how cases are distributed across categories. The article further explores the justification for employing a 50% benchmark in interpreting survey responses, drawing connections to established research practices. The analysis demonstrates that these descriptive statistics are not merely convenient but are methodologically appropriate for addressing research questions involving categorical variables.