Statistics is concerned with both qualitative and quantitative information.

Qualitative Information

Qualitative information is descriptive data that cannot be measured numerically. It is concerned with the qualities, characteristics, and properties of a phenomenon. Examples of qualitative information include:

- Colors
- Tastes
- Shapes
- Smells
- Opinions
- Attitudes
- Emotions

In statistics, qualitative information is often represented using nominal or ordinal scales.

Quantitative Information

Quantitative information is numerical data that can be measured and analyzed statistically. It is concerned with the quantities, amounts, and magnitudes of a phenomenon. Examples of quantitative information include:

- Height
- Weight
- Age
- Income
- Temperature
- Time
- Distance

In statistics, quantitative information is often represented using interval or ratio scales.

Why Both are Important?

Both qualitative and quantitative information are important in statistics because they provide different types of information that can help us understand a phenomenon. Qualitative information can provide insights into the attitudes, beliefs, and experiences of people, while quantitative information can provide precise measurements and statistical analyses that can help us make predictions and decisions. In many cases, a combination of both qualitative and quantitative information is needed to fully understand a phenomenon.