Quantitative Vs. Qualitative Data – Definition

Qualitative data is information focused on descriptions that can be witnessed but cannot be computed. On the other hand, quantitative information focuses on numbers and mathematical calculations and can be calculated.
So, the collection of data and evaluation may be done using any of the two methods indicated above.
Both have strengths and weaknesses: for example, qualitative data fail 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 identical data units, 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	Data that deal with quantities, values, or numbers.	Data 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	Statistics add credence or credibility to it so that quantitative data is 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

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.

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 organized, but only to a very small, restricted degree.
Typically, conducting qualitative research costs a lot of money and time, so researchers often try to save expenses by reducing the sample size or the number of respondents.