What is Discrete Data?
Discrete data is defined as values that are whole numbers, finite and distinct from each other.
For example, the number of students in 4 different classrooms will get values such as 10, 14, 7, 8. Note that each number here represents a value that is a whole number (you cannot have 10.3 students) with no decimals, and each value has no relationship with another value (counting of students in one classroom doesn’t affect the counting of another classroom). And it’s a finite number.
This is why they are called “discrete” data, since each value is independent of any other value and can exist discretely.
Key Characteristics of Discrete Data
Here are the key characteristics of discrete data:
- Countable and finite values:
Discrete data always has a countable finite value, as it remains discrete only in relationship with another value.
For example, just the number of cars in a parking lot A would yield a number say 45. Now 45 in and of itself is not a discrete data, it’s just a whole number. Now if compared to other parking lots, say B and C, say the numbers turn out to be 45, 56, 28, then each number is a discrete number in relationship with the whole set, and there are no values in between each, and are hence finite.
- Distinct and separate values:
Each value in discrete data is distinct and separate from others. There are clear gaps between these values, meaning you cannot find a value in between two discrete data points.
In the example from above, the values of the number of cars in parking lot A, B and C are 45, 56, 28 respectively. There is no value in between 45 and 56 for instance, and hence there is no continuity to connect them.
- Whole number representation:
Discrete data is always represented by whole numbers and has no room for fractions and decimals.
From the example we are following from above, the value of the number of cars in a parking lot cannot be 45.6 or 45 1⁄2 for instance.
Examples of Discrete Data
Here are several examples of discrete data that illustrate how it is used in various contexts:
- Number of students in a classroom:
This is a common example where the value is a countable number. For instance, a classroom can have 20, 21, or 22 students, but it cannot have 20.5 students. Each value represents a whole person.
- Number of cars in a parking lot:
The count of cars in a parking lot is another example of discrete data. The number could be 50, 51, or 52, but it cannot be a fraction. Each car represents a whole unit that is counted.
- Number of heads in a series of coin flips:
When flipping a coin multiple times, the number of times it lands on heads is discrete data. If you flip a coin 10 times, you might get 0, 1, 2, up to 10 heads, but you can never get 2.5 heads.
- Number of books in a library:
Libraries often count the number of books they have. The number could be 5,000, 5,001, or 5,002, but not 5,000.5. Each book is a discrete entity that can be counted.
- Scores in a game:
Scores achieved by players in a game, such as a basketball match, are discrete. A team might score 98, 99, or 100 points, but not 98.7. The scores represent distinct, whole numbers.
- Number of children in a family:
The count of children in a family is another example of discrete data. A family might have 1, 2, 3, or more children, but not 1.5 children.
- Number of pets owned:
The number of pets owned by a person or family is discrete. This count can be 0, 1, 2, and so on, but it cannot be a fraction or decimal.
