Quantitative vs. Qualitative Data: 13 Differences, Examples

Difference between Quantitative and Qualitative Data

Quantitative and Qualitative Data Definition

Qualitative data is data concerned with descriptions, which can be observed but cannot be computed. On the contrary, quantitative data is the one that focuses on numbers and mathematical calculations and can be calculated and computed.

  • So, for the collection and measurement of data, any of the two methods discussed above can be used.
  • Although both have its merits and demerits, i.e. while qualitative data lacks reliability, quantitative data lacks a description.
  • Both are used in conjunction so that the data gathered is free from any errors.
  • Further, both can be acquired from the same data unit only their variables of interest are different, i.e. numerical in case of quantitative data and categorical in qualitative data.

Read Also: Data and its types

Key Differences (Quantitative vs Qualitative Data)

S.N. Character Quantitative Data Qualitative Data
1.       Definition These are data that deal with quantities, values, or numbers. These data, on the other hand, deals with quality.
2.       Measurability Measurable. They are generally not measurable.
3.       Nature of Data Expressed in numerical form. They are descriptive rather than numerical in nature.
4.       Research Methodology Conclusive Exploratory
5.       Quantities measured Measures quantities such as length, size, amount, price, and even duration. Narratives often make use of adjectives and other descriptive words to refer to data on appearance, color, texture, and other qualities.
6.       Method of collection


Statistics is used to generate and subsequently analyze this type of data. They are only gained mostly through observation.
7.       Approach Objective  Subjective
8.       Data Structure Structured Unstructured
9.       Determines Level of occurrence Depth of understanding
10.    Reliability The uses of statistics add credence or credibility to it so that quantitative data is overall seen as more reliable and objective. Less reliable and objective.
11.    Data Collection Techniques Quantitative surveys, Interviews, Experiments Qualitative surveys,  Focus group methods, Documental revision, etc.
12.    Sample A large number of representative samples A small number of non-representative samples
13.    Outcome Develops initial understanding Recommends the final course of action

Quantitative Data Collection Methods

  • Data can be readily quantified and generated into numerical form, which will then be converted and processed into useful information mathematically.
  • The result is often in the form of statistics that is meaningful and, therefore, useful.
  • Unlike qualitative methods, these quantitative techniques usually make use of larger sample sizes because its measurable nature makes that possible and easier.

Qualitative Data Collection Methods

  • Exploratory in nature, these methods are mainly concerned at gaining insights and understanding of underlying reasons and motivations, so they tend to dig deeper.
  • Since they cannot be quantified, measurability becomes an issue.
  • This lack of measurability leads to the preference for methods or tools that are largely unstructured or, in some cases, maybe structured but only to a very small, limited extent.
  • Generally, qualitative methods are time-consuming and expensive to conduct, and so researchers try to lower the costs incurred by decreasing the sample size or number of respondents.


  1. https://www.cleverism.com/qualitative-and-quantitative-data-collection-methods/
  2. https://keydifferences.com/difference-between-qualitative-and-quantitative-data.html
  3. https://www.skillsyouneed.com/learn/quantitative-and-qualitative.html
  4. https://www.surveymonkey.com/mp/quantitative-vs-qualitative-research/
  5. https://www.managementnote.com/types-of-data

About Author

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Sagar Aryal

Sagar Aryal is a microbiologist and a scientific blogger. He is doing his Ph.D. at the Central Department of Microbiology, Tribhuvan University, Kathmandu, Nepal. He was awarded the DAAD Research Grant to conduct part of his Ph.D. research work for two years (2019-2021) at Helmholtz-Institute for Pharmaceutical Research Saarland (HIPS), Saarbrucken, Germany. Sagar is interested in research on actinobacteria, myxobacteria, and natural products. He is the Research Head of the Department of Natural Products, Kathmandu Research Institute for Biological Sciences (KRIBS), Lalitpur, Nepal. Sagar has more than ten years of experience in blogging, content writing, and SEO. Sagar was awarded the SfAM Communications Award 2015: Professional Communicator Category from the Society for Applied Microbiology (Now: Applied Microbiology International), Cambridge, United Kingdom (UK).

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