Statistics for Everyday Life
Discrete vs Continuous Data
Knowing whether your data is discrete or continuous decides which charts, summaries, and methods are appropriate. The distinction is about counting versus measuring.
| Aspect | Discrete data | Continuous data |
|---|---|---|
| How you get it | Counting | Measuring |
| Possible values | Distinct, separate (often whole numbers) | Any value within a range, including fractions |
| Between two values | Gaps — no values in between | Infinitely many possible values in between |
| Examples | Number of children, cars sold, dice rolls | Height, weight, temperature, time |
| Typical chart | Bar chart | Histogram or line graph |
When to use discrete data
Data is discrete when it comes from counting distinct items — you can’t have 2.5 children — and is usually shown with bar charts.
When to use continuous data
Data is continuous when it comes from measuring on a scale — height or time can take any value — and is usually shown with histograms.
Frequently asked questions
- Is money discrete or continuous?
- It’s a common edge case. Strictly, money comes in smallest units (cents), making it discrete, but it’s often treated as continuous because the units are so fine relative to the amounts. Context decides which treatment is more useful.
- Why does the difference matter?
- It guides your choices: which graphs to use (bar chart vs histogram), which summary statistics make sense, and which probability models apply. Using a continuous method on truly discrete data (or vice versa) can mislead.
- Are age and shoe size discrete or continuous?
- Age is continuous (it increases smoothly, even if we report whole years). Shoe sizes are discrete because they come in fixed steps. How data is recorded can differ from its underlying nature.