Data reduction

Process (computing)

Engineering

Philosophy

Data collection

Interpretation (philosophy)

Operating system

Data mining

Computer science

Qualitative property

Management science

Qualitative research

Mathematics

Epistemology

Domain (mathematical analysis)

Sociology

Mathematical analysis

Data science

Programming language

Qualitative analysis

Data analysis

Machine learning

Social science

Research on Humanities and Social Sciences

This paper intends to present the practical aspects of doing qualitative data analysis. To this end, the paper was compiled to understand the practical aspects of doing qualitative data analysis with the ultimate purpose of identifying the commonly used approaches and techniques for data reduction, data display, and interpretation. Secondary source of data was used to collect and analyze the data needed to address the aforementioned objectives. Accordingly, books, articles, research reports, and different published materials were critically reviewed. The paper began by defining what qualitative data analysis is in accordance with its aim, basic principles and features. In addition, the paper presents qualitative data analysis and its philosophical foundations on the basis of ontological and epistemological stance. The paper further discuss the most commonly used approaches to analyze qualitatively collected data focusing on the background and philosophical basis of each method, unique characteristics of each method, goals and rationale of each method and data analysis process of each method. The paper has also disclosed ethical issues to be considered on the process of qualitative data analysis. The arguments on the paper have by and large proved to be very helpful for analyzing qualitatively collected data in the domain of humanities and social Science inquiries. Keywords: Qualitative Data Analysis, Data Reduction, Data Display, and Data Interpretation. DOI: 10.7176/RHSS/10-21-02 Publication date: November 30 th 2020

Qualitative Data Analysis: An Overview of Data Reduction, Data Display and Interpretation