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Understanding how variables types could be qualitative x quantitative
Types of Variables
Types of Variables
The values of a variable could vary in its nature: quantitative or qualitative.
A quantitative variable means its values can be measured numerically and will be:
1. Discrete: 0, 1, 2, 3.
2. Continuous: 43.32 or [6.5; 7.8].
A qualitative variable means it describes data that fit into categories that may or may not be sequential. For example:
1. Quality: Very good, good, bad, very bad.
2. States: Florida, New Jersey, Washington.
As a general rule, if you can apply some kind of math (like addition), it’s a quantitative variable. Otherwise, it’s qualitative.
The next Figure summarizes previous definitions of data extraction from an element or a member.
The next Figure illustrates the connection between elements, variables, observations, and data sets.
Since we learned new terms, now it is time how to transform them into a more representative group of elements like tables, graphics, and summary metrics. These three groups make possible the process to consolidate a large amount of raw data into small and visual information. Just to illustrate, two summary metrics are mean (a measure of central tendency) and standard deviation (a measure of dispersion).
The word for this consolidated information that summarizes some properties and patterns from the original data is Descriptive Statistics.
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