What is the difference between quantitative and qualitative data?

Quantitative data is defined as numerical data that can be measured and expressed in numbers, making it suitable for statistical analysis. This type of data allows for the calculation of various metrics, such as averages, sums, and percentages, and is often used to facilitate comparisons across different sets of information. For example, data such as "25 students scored 80 out of 100" is quantitative because it involves numerical values that can be analyzed statistically.

On the other hand, qualitative data refers to non-numeric information that describes characteristics, attributes, or properties. It is often collected through observations, interviews, or open-ended survey questions, and is typically analyzed through thematic or content analysis rather than through statistical methods. For example, responses to the question "What do you think about your school?" would yield qualitative data since the answers would describe opinions or feelings rather than measurable quantities.

The distinction between these two types of data is crucial in data analysis because it dictates the methods of analysis applied and influences the types of conclusions that can be drawn from the data.