Compare and Contrast

Qualitative Vs Quantitative Research

Qualitative Vs Quantitative Research

Qualitative Vs Quantitative Research

Qualitative research and quantitative research are two different approaches used in conducting research. Here’s a brief explanation of the differences between the two:


Qualitative Research is exploratory research that seeks to understand a phenomenon in its natural setting from the perspective of the people involved. It uses methods like interviews, focus groups, and observation to gather data.

Quantitative Research is structured research that focuses on measuring and analyzing numerical data. It uses methods like surveys, experiments, and statistical analysis to gather and analyze data.

Data Collection

Qualitative Research uses non-numeric data, such as words, images, and observations, to gather data. This data is often subjective and can be difficult to analyze.

Quantitative Research, on the other hand, uses numerical data, such as survey responses or experimental measurements, to gather data. This data is objective and easier to analyze.

Data Analysis

Qualitative Research uses an interpretive approach to analyze data, meaning that the researcher is interested in understanding the meaning behind the data. This often involves identifying patterns, themes, and relationships in the data.

Quantitative Research, on the other hand, uses statistical analysis to identify patterns and relationships in the data. This involves using mathematical formulas and statistical tests to analyze the data.


Qualitative Research is often used to gain a deeper understanding of a phenomenon or to generate hypotheses for further research. It is commonly used in fields like anthropology, sociology, and psychology.

Quantitative Research is often used to test hypotheses or to make predictions about a phenomenon. It is commonly used in fields like economics, engineering, and biology.

Differences between Qualitative and Quantitative Research

AspectQualitative ResearchQuantitative Research
Data typeNon-numeric (words, images, observations)Numeric (surveys, experiments, measurements)
Data collectionOpen-ended, flexible, interactive (interviews, focus groups, observation)Structured, standardized, fixed (surveys, experiments)
Sample sizeSmall and non-randomLarge and often random
Data analysisInterpretive, inductive, exploratory (identifying patterns, themes, and relationships)Statistical, deductive, confirmatory (testing hypotheses, making predictions)
PurposeGain a deeper understanding of a phenomenon, generate hypothesesTest hypotheses, make predictions
Research contextNatural settings, subjective experiences, complex phenomenaControlled settings, objective measurements, simpler phenomena
ExamplesAnthropology, sociology, psychologyEconomics, engineering, biology

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer