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Quantitative Vs Qualitative Data- Definition, 13 Differences, Examples

Quantitative Vs Qualitative Data Definition

  • Qualitative data is information which is focused on descriptions that can be witnessed but cannot be computed. On the other hand, quantitative information is the kind that focuses on numbers and mathematical calculations and can be calculated.
  • So, collection of data and evaluation may be done using any of the two methods indicated above.
  • All have benefits and drawbacks; for example, qualitative data fails reliability tests, whereas quantitative data without a description does not.
  • Both are merged to make sure that the information gathered is error-free.
  • Both can be produced from the identical data unit, but the variables of interest for every are different; for qualitative data, they are categorical, while for quantitative data, they are numerical.

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

  • It is simple to quantify data and convert it to numerical form, which can then be mathematically evaluated and translated into helpful data.
  • The result is typically statistics that are significant and thus important.
  • Because of the measurable nature of the information, these quantitative approaches frequently use bigger sample sizes than qualitative ones.

Qualitative Data Collection Methods

  • These methods, which have an exploratory focus, tend to go deeper since their primary goal is to get insights into and knowledge of the underlying causes and motives.
  • Measurability becomes a problem since they are not quantifiable.
  • This absence of measurability leads to the demand for processes or instruments which are essentially unstructured or, in certain circumstances, somewhat organised, but only to a very small, restricted degree.
  • Typically, conducting qualitative research costs a large amount of money and time, so researchers often try to save expenses by reducing the sample size or number of respondents.

References

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