But unless you classify in this manner, you cannot handle the people in groups. Every collection can be classified in many different ways. More than one dimension of classification is necessary if more than one dimension helps to distinguish various groups or to predict their behavior. But there is no value in having two dimensions if both classify all occurrences in the same way. For example, if all candidates for the baseball team who throw hard also throw far, and vice versa, a judgment of whether a player either throws hard or throws far will be sufficient.
Categories can employ either words or numbers.
It is possible to go from words to numbers or the reverse, though the process is not symmetrical. In this way you have converted 'quantitative' data into 'qualitative' verbal categories. The numerical cut-off points for the categories should be those that are most useful for you. Defining categories is a progressive process. As tough instances come along, you sit down and relate them to your final purpose and then amend your definitions to cover them.