Numbers vs Words : Quantitative and Qualitative Data Explained

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Russian nesting dolls make for a great analogy of ordinal data, where each subsequent doll is larger or smaller than the previous one, representing a ranking or order


As someone with a background in natural sciences, I have a solid understanding of the difference between quantitative and qualitative data.

Quantitative data is anything that can be measured - for example, the atmospheric pressure can be measured using a barometer. It's the kind of data that can answer life's most pressing questions, such as 'How many more hours until Friday?' and 'How much caffeine from Starbucks is too much?'

On the other hand, qualitative analysis provides a description of something - for instance, you may have brown hair and be of Asian descent.

However, these two categories of data are like Russian nesting dolls that can be further divided into sub-categories that unpack the characteristics of the data even more.

Here are the respective subcategories of quantitative and qualitative data:


Qualitative Data

Nominal Data 

The word 'nominal' may sound like a fancy, but really it's just a  Latin term that means 'name'. Let's be real, sometimes we just need to put a label on things, like our marital status or gender.

Ordinal Data 

Ordinal data is like a ranking system, but don't try to crunch numbers with it. It's like ranking drinks as "sorrel first", "mauby second", and "orange juice third" - you can't add them up.

Quantitative Data 

Discrete Data

Let's say you're keeping track of the number of pets your friends have. You can only count in whole numbers, so you have discrete data. You can't have half a turtle or a quarter of a dog!

Continuous Data 

Continuous data is like a flowing river, always changing and never stopping. Think of measuring the temperature - it can be 20.1°C at one point, and then 22.4°C the next.


Resources 



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