REASON FOR USING FREQUENCY AND PERCENTAGE TO ANALYSE CATEGORICAL DATA

Categorical data are widely generated in educational, social, management, health and behavioural research, particularly through questionnaires and surveys. Such data classify respondents into distinct groups or response categories, including sex, marital status, educational qualification, yes/no responses and levels of agreement on Likert scales. Frequency and percentage are among the most appropriate descriptive statistical techniques for summarising categorical data. Frequency shows the number of observations in each category, while percentage expresses the frequency as a proportion of the total valid observations. This article examines the reasons for using frequency and percentage to analyse categorical data regardless of the degree or educational level of respondents. It also discusses the use of a 50% benchmark for interpreting data collected through both non-Likert and Likert-scale instruments

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-08-17
DOI
https://doi.org/10.5281/zenodo.21984596
Primary Topic
Sensory Analysis and Statistical Methods
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

REASON FOR USING FREQUENCY AND PERCENTAGE TO ANALYSE CATEGORICAL DATA

Best Osuji
Zenodo (CERN European Organization for Nuclear Research)
Sensory Analysis and Statistical Methods
article

REASON FOR USING FREQUENCY AND PERCENTAGE TO ANALYSE CATEGORICAL DATA

Best Osuji
article en

Abstract

Categorical data are widely generated in educational, social, management, health and behavioural research, particularly through questionnaires and surveys. Such data classify respondents into distinct groups or response categories, including sex, marital status, educational qualification, yes/no responses and levels of agreement on Likert scales. Frequency and percentage are among the most appropriate descriptive statistical techniques for summarising categorical data. Frequency shows the number of observations in each category, while percentage expresses the frequency as a proportion of the total valid observations. This article examines the reasons for using frequency and percentage to analyse categorical data regardless of the degree or educational level of respondents. It also discusses the use of a 50% benchmark for interpreting data collected through both non-Likert and Likert-scale instruments

Zenodo (CERN European Organization for Nuclear Research)
Gender equality
Openalex Percentile: Top 12%
Sensory Analysis and Statistical Methods
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.