Quantitative v/s Qualitative data

Quantitative data :Quantitative data can be defined as the data which gives the information in some quantitative form or in measurable form. We can write the quantitative data in the form of numbers (example your height, weight, age etc.) and can apply various mathematical and statistical formulas on it which can help in business decision making at various levels.This type of data is closed-ended and is generally easy to analyse. It is important to note that Quantitative data can be discrete or continuous.

Qualitative data :On the other hand Qualitative data can be defined as the data which gives the information in the form of some descriptions in a language rather than in numbers. This type of data can be observed but cannot be measured (example – color, taste, appearance etc.) but it can also help in taking business decisions under various circumstances.This type of data is open-ended and is more difficult for analysis. It is interesting to know that different analysts can draw different conclusions from the same qualitative data.

Drawbacks and Importance :Quantitative data can provide information about large size of population but does not provide in depth knowledge about a particular entity, so it is backed or supported by qualitative data. Where qualitative data can provide information about a particular thing or issue but is criticized for its unreliability, so it is supported by quantitative data. That is why both qualitative and quantitative type of data is used in any research.