REASON FOR USING FREQUENCY AND PERCENTAGE TO ANALYSE CATEGORICAL DATA

Categorical data occur widely in social science, education, management, information management and other fields where observations are classified into groups or response categories. Because such data are expressed as categories rather than continuous numerical measurements, frequency and percentage are among the most appropriate first-level descriptive methods. Frequency shows the actual number of observations in each category, while percentage expresses those observations as a proportion of the total. This makes findings easier to understand, compare and communicate. This article explains the reasons for using frequency and percentage with categorical data, including both non-Likert and Likert-scale responses. It also discusses the practical use of a 50% benchmark where the researcher wants to determine whether a majority of respondents support a position. An aviation example is used to demonstrate the application of the methods. The article concludes that frequency and percentage provide transparent and accessible descriptions of categorical responses, but should be supplemented with appropriate inferential statistics when the research objective involves testing relationships, differences or statistical significance.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-08-18
DOI
https://doi.org/10.5281/zenodo.21997624
Primary Topic
Environmental and Air Quality Management
Type
article
Field-Weighted Citation Impact
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article

REASON FOR USING FREQUENCY AND PERCENTAGE TO ANALYSE CATEGORICAL DATA

MAUREEN OMEDE
Zenodo (CERN European Organization for Nuclear Research)
Environmental and Air Quality Management
article

REASON FOR USING FREQUENCY AND PERCENTAGE TO ANALYSE CATEGORICAL DATA

MAUREEN OMEDE
article en

Abstract

Categorical data occur widely in social science, education, management, information management and other fields where observations are classified into groups or response categories. Because such data are expressed as categories rather than continuous numerical measurements, frequency and percentage are among the most appropriate first-level descriptive methods. Frequency shows the actual number of observations in each category, while percentage expresses those observations as a proportion of the total. This makes findings easier to understand, compare and communicate. This article explains the reasons for using frequency and percentage with categorical data, including both non-Likert and Likert-scale responses. It also discusses the practical use of a 50% benchmark where the researcher wants to determine whether a majority of respondents support a position. An aviation example is used to demonstrate the application of the methods. The article concludes that frequency and percentage provide transparent and accessible descriptions of categorical responses, but should be supplemented with appropriate inferential statistics when the research objective involves testing relationships, differences or statistical significance.

Zenodo (CERN European Organization for Nuclear Research)
Quality Education
Openalex Percentile: Top 16%
Environmental and Air Quality Management
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REASON FOR USING FREQUENCY AND PERCENTAGE TO ANALYSE CATEGORICAL DATA — MAUREEN OMEDE · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS