Understanding Data Types: Qualitative vs. Quantitative

Data can be classified into two types: qualitative and quantitative.

Qualitative data refers to non-numeric information, focusing on attributes or qualities.

Quantitative data is numerical and allows for mathematical operations.

Examples of qualitative data include hair color, eye color, ethnicity, religion, and political affiliation.

Qualitative data can also be referred to as categorical data.

Quantitative data is numerical and can be used for mathematical calculations.

It is categorized into discrete and continuous data: discrete data is countable, while continuous data can take on an infinite number of values.

The four levels of measurement are nominal, ordinal, interval, and ratio.

Nominal data categorizes with no inherent order, ordinal data allows for ranking but with meaningless differences.

Interval data has meaningful differences but lacks a natural zero, whereas ratio data has both meaningful differences and a natural zero.