Types of Data
Start with the variable: the thing recorded for one person or object. How that value is produced tells you the data type.
Ask how one value was produced
words or categories
qualitative
blood group → bar chart or pie chart
counted or fixed steps
discrete
number of goals → stem-and-leaf or bar chart
measured on a scale
continuous
time or mass → histogram or cumulative-frequency graph
First separate categories from numbers
- Qualitative data, also called categorical data, uses labels such as blood group, colour or method of travel.
- Quantitative data uses numerical values. It then divides into discrete and continuous data.
A category may be written as a number, such as a bus route number. It is still qualitative if the number is only a label.
Then ask: counted or measured?
| Type | How values arise | Examples |
|---|---|---|
| discrete | counted, or restricted to separate allowed values | number of goals; shoe sizes sold in half-sizes |
| continuous | measured; any value in an interval is possible | time; mass; exact height |
Discrete data comes from counting or fixed steps. Continuous data comes from measurement across an interval.
A continuous measurement stays continuous after rounding. A recorded height of 172 cm could represent many actual heights near 172 cm.
Common mistake
Now you try
Classify each variable as qualitative, discrete or continuous: eye colour; number of siblings; bus route used; shoe size sold in half-size steps; exact temperature; mass recorded to the nearest gram.
Show worked answer
- Eye colour: qualitative.
- Number of siblings: discrete.
- Bus route used: qualitative; its number is a label.
- Shoe size in fixed half-size steps: discrete.
- Exact temperature: continuous.
- Rounded mass: continuous; the underlying measurement can take any value in an interval.