Understanding Continuous and Discrete Data
In statistics, a type of data is collectively referred to as a variable. The data of a variable is called an observation, and the specific value of a variable is known as an observed value. For example, in the data below, age and name are variables, while 18 and 'Dahong' are specific observed values.
age, name
18, ‘Dahong’
21, ‘Xiaohua’
Similarly, in statistics, discrete data is also referred to as discrete variables, and continuous data is called continuous variables. But how do we distinguish between the two?
Continuous variables can theoretically take values continuously without interruption, while discrete variables take values in discontinuous intervals. The distinction is not about the number of possible values—both can have infinitely many.
For example:
- The number of people in a household is a discrete variable because it can only take whole numbers like 1, 2, 3, or 4. It cannot be 1.2, 1.8, or 2.4 people.
- Age, on the other hand, is a continuous variable. While we often simplify age to whole numbers like 18, 17, or 30 years for convenience, age can take precise values like 18.32, 17.55, or 30.67 years. For example, 17.55 years represents 17 years, 6 months, and 18 days, and age can even be measured to the exact hour, minute, or second.