Why Data Classification Comes Before Analysis
Before any calculation, graph, or model, a statistician must answer a basic question: What kind of data is this?
Different data types demand different summaries, visualizations, and conclusions. Treating all data as “numbers” is one of the most common and damaging mistakes in statistics.
This lecture develops disciplined thinking about data types and measurement scales.
Data can be broadly classified into two categories based on meaning.
Quantitative data represent numerical measurements or counts.
Qualitative data represent categories, labels, or attributes.
The difference is not cosmetic. It determines what operations are meaningful.
Quantitative data arise when numbers represent magnitude or amount.
Examples include:
Arithmetic operations make sense because the numbers measure quantity.