Data Categories

To analyze data effectively, it is important to understand the types of data involved.

Data can be categorized into two main types:

1. Quantitative Data: Numerical data that can be measured or counted. It is further divided into:

   • Discrete Data: Whole numbers, such as the number of students in a class or goals in a soccer game.
   • Continuous Data: Values with infinite precision, such as a person’s weight, shoe size, or temperature.

2. Qualitative Data: Non-numerical data that cannot be measured. It is further divided into:

   • Nominal Data: Categories without a specific order, such as gender, hair color, or ethnicity.
   • Ordinal Data: Categories with a meaningful order, such as school grades (A, B, C) or economic status (low, middle, high).

Understanding the type of data helps determine the appropriate analysis techniques to apply.