Data Types: Continuous and Discrete¶
Continuous data¶
Continuous data can take any value within a range (including decimals). It is typically measured.
Examples:
- Height (cm)
- Weight (kg)
- Time (seconds)
- Temperature (°C)
Common visualizations:
- Histogram
- Density plot
- Box plot
Discrete data¶
Discrete data takes distinct, countable values (usually integers). It is typically counted.
Examples:
- Number of students in a class
- Number of goals scored
- Number of defects in a batch
Common visualizations:
- Bar chart
- Count plot
Quick comparison¶
| Feature | Continuous | Discrete |
|---|---|---|
| Values | Any real value in an interval | Separate, countable values |
| Source | Measurement | Counting |
| Examples | height, weight, time | number of items, number of events |
Why it matters¶
Choosing the right statistical method depends on the data type.
- Continuous variables commonly use:
- mean, variance, standard deviation
- correlation, regression
- Discrete/count variables commonly use:
- frequency tables
- binomial, Poisson models