Quantitative & Qualitative Data
There are two types of data, quantitative and qualitative. Generally speaking, when you measure something and give it a number value, you create quantitative data. When you classify or judge something, you create qualitative data. There are also different types of quantitative and qualitative data. (Also see, Qualitative vs Quantitative Data article.)
Qualitative Data
Qualitative data is used to characterize objects or observations, which can be collected in a non-numerical and non-binary way, such as languages. Qualitative data can include:
Text
Audio and video recordings
Experiment notes, lab reports
Interview transcripts
Two types of qualitative data include categorical, meaning data that can be organized in groups, and ordinal, meaning qualitative data that follows a natural order.
Categorical | Ordinal |
States (e.g., New York, Massachusetts, Arizona) | Economic class (e..g, lower class, middle class, higher class) |
People names (e.g., Matt, Emily, Maria) | Satisfaction scale (e.g., extremely dislike, dislike, neutral, like, extremely like) |
Brands (e.g., Coke, Pepsi, Dr. Pepper) | Sports medals (e.g., gold, silver, bronze) |
Quantitative Data
Quantitative data, as the name suggests, relates to the quantity of something, and typical examples of quantitative data are numbers. Quantitative data can include:
Surveys data, including longitudinal and cross-sectional studies
Count frequency
Calculations such as calculating monthly gross margin
Quantification: converting descriptive data to numbers such as satisfaction rating from 1-4
Two types of quantitative data include continuous, meaning numbers that can be made more precise and divided, e.g, a 4.3 earthquake, and discrete, meaning numbers that cannot be divided, e.g., the number of people in a household cannot include a fraction such as 3.5.
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