Which type of data can be measured or counted?

Quantitative data refers to information that can be measured or counted, making it inherently numerical in nature. This data type allows researchers and practitioners to perform statistical analyses because it consists of values that represent quantities, such as age, income, or the number of items sold. Each of these can be subjected to mathematical operations, allowing for a deeper analysis of trends, means, medians, and other statistical measures.

In contrast, qualitative data typically represents categories or qualities that describe characteristics but do not have numerical values associated with them. This means qualitative data cannot be reliably counted or measured in the same way quantitative data can. Similarly, nominal and ordinal data are subcategories of qualitative data. Nominal data categorizes without any specific order (like colors or types of pets), while ordinal data involves categories that have a specific rank or order (like customer satisfaction rankings), but still do not lend themselves to direct measurement or counting in a quantifiable manner. Thus, quantitative data stands out as the only type that possesses the ability to be measured or counted effectively.