What is the difference between qualitative and quantitative data?

Qualitative data is descriptive in nature, focusing on characteristics, qualities, and attributes that cannot be easily measured in numerical terms. This type of data often captures opinions, feelings, or descriptions about a subject and is typically gathered through interviews, open-ended surveys, and observational methods. For example, qualitative data might include descriptions of the taste of food, customer satisfaction, or the color of a flower.

On the other hand, quantitative data is numerical and represents measurable quantities. It allows for statistical analysis and can be collected through methods such as surveys with rating scales, experiments, and measurements that result in numerical outcomes. An example of quantitative data would be the temperature of food in degrees, the number of customers in a store, or the weight of an ingredient.

Understanding this distinction is critical as it influences how researchers collect, analyze, and interpret data. While both types of data can provide valuable insights, they serve different purposes and are used in varying contexts within research and practice.