How is statistical data categorized?

Statistical data can be categorized in several ways, including:

1. Qualitative data: Data that describes qualities or characteristics and cannot be measured numerically. Examples include gender, ethnicity, and occupation.

2. Quantitative data: Data that can be measured and expressed numerically. This can be further divided into discrete data (countable and finite values) and continuous data (infinite and uncountable values).

3. Primary data: Data that is collected firsthand by the researcher through surveys, experiments, or observations.

4. Secondary data: Data that has been collected and published by someone else, such as government agencies, research institutions, or other organizations.

5. Cross-sectional data: Data collected at a single point in time.

6. Time-series data: Data collected over a period of time to track changes and trends.

7. Categorical data: Data that can be divided into categories or groups, such as age groups or types of products.

8. Numerical data: Data that consists of numbers and can be further divided into discrete or continuous data.

9. Ordinal data: Data that has a natural order or ranking, such as ratings or rankings.

10. Interval data: Data that has equal intervals between values but no true zero point, such as temperature measurements in Celsius or Fahrenheit.

11. Ratio data: Data that has equal intervals between values and a true zero point, such as weight or height measurements.