Discrete data and continuous data?

Discrete data refers to data that can only take on specific values and cannot be broken down into smaller units. Examples of discrete data include the number of students in a class, the number of cars in a parking lot, or the number of books on a shelf.

Continuous data, on the other hand, refers to data that can take on any value within a certain range. Examples of continuous data include height, weight, temperature, and time. Continuous data can be measured and broken down into smaller units, such as measuring temperature in degrees Celsius or measuring time in seconds.

Discrete Data

- Represents data that takes on a finite set of distinct values.
- Can be counted in whole numbers.
- Examples:
- Number of students in a class
- Number of days in a week
- Number of items sold in a store

Continuous Data

- Represents data that can take on any value within a certain range.
- Can be measured to any degree of precision.
- Examples:
- Height of a person
- Temperature of a room
- Weight of an object

Key Differences

| Feature | Discrete Data | Continuous Data |
|---|---|---|
| Values | Finite set of distinct values | Any value within a range |
| Counting | Can be counted in whole numbers | Cannot be counted in whole numbers |
| Measurement precision | Limited to whole numbers | Can be measured to any degree of precision |
| Data type | Usually integers | Usually real numbers |
| Frequency | Can be represented as a frequency distribution | Can be represented as a probability distribution |

Examples

- Discrete data: Number of cars in a parking lot, number of people at a party, number of wins for a sports team.
- Continuous data: Age of a person, height of a building, temperature of a lake.