Quantitative vs Qualitative Data, Defined

January 4, 2022

Sounding almost philosophical, The Future of Things posts, “What is Data? Types of Data, Explained.” Distinguishing between types of data can mean many things. One distinction we are always curious about is what data does one emit via mobile devices and what types are feeding the surveillance machines? This write-up, though, is more of a primer on a basic data science concept: the difference between quantitative and qualitative data. Writer Kris defines quantitative data:

“As the name suggests, quantitative data can be quantified — that is, it can be measured and expressed in numerical values. Thus, it is easy to manipulate quantitative data and represent it through statistical graphs and charts. Quantitative data usually answers questions like ‘How much?’, ‘How many?’ and ‘How often?’ Some examples of quantitative data include a person’s height, the amount of time they spend on social media and their annual income. There are two key types of quantitative data: discrete and continuous.”

Here is the difference between those types of quantitative data: Discrete data cannot be divided into parts smaller than a whole number, like customers (yikes!) or orders. Continuous data is measured on a scale and can include fractions; the height or weight of a product, for example.

Kris goes on to define quantitative data, which is harder to process and analyze but can provide insights that quantitative data simply cannot:

“Qualitative data … exists as words, images, objects and symbols. Sometimes qualitative data is called categorical data because the information must be sorted into categories instead of represented by numbers or statistical charts. Qualitative data tends to answer questions with more nuance, like ‘Why did this happen?’ Some examples of qualitative data business leaders might encounter include customers’ names, their favorite colors and their ethnicity. The two most common types of qualitative data are nominal data and ordinal data.”

As the names suggest: Nominal data names a piece of data without assigning it any order in relation to other pieces of data. Ordinal data ranks bits of information in an order of some kind. The difference is important when performing any type of statistical analysis.

Cynthia Murrell, January 4, 2022

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