Qualitative vs. Quantitative


by William M.D. Trochim (synopsis)

There has probably been more energy expended on debating the differences between and relative advantages of qualitative and quantitative methods than almost any other methodological topic in social research. The qualitative-quantitative debate can trigger an intense debate.
To say that one or the other approach is "better" is a trivializing of a far more complex topic than a dichotomous choice. In most applied social research project there is value in combining both qualitative and quantitative methods in what is referred to as a "mixed methods" approach.

It is important to distinguish between the general assumptions involved in undertaking a research project and the data that are collected. At the level of the data there is little difference between the qualitative and the quantitative. At the level of the assumptions that are made, the differences can be profound and irreconcilable.
Qualitative data typically consists of words while quantitative data consists of numbers. However, all qualitative data can be coded quantitatively. Anything that is qualitative can be assigned meaningful numerical values. These values can be manipulated to achieve greater insight into the meaning of the data and examine specific hypotheses.

Many surveys have one or more short open-ended questions that ask the respondent to supply text responses. The simplest example is probably the "Please add any additional comments" question that is often tacked onto a short survey. The immediate responses are text-based and qualitative, but we usually perform some type of simple classification of the text responses. We can sort the responses into simple categories. Often, we'll give each category a short label that represents the theme in the response.

The quantitative coding gives us additional useful information that makes it possible to do analyses which we could not do otherwise. The line between qualitative and quantitative is not distinct. All qualitative data can be quantitatively coded. This doesn't detract from the qualitative information. We can still do any kinds of judgmental syntheses or analyses we want. Recognizing the similarities between qualitative and quantitative information opens up new possibilities for interpretation that might otherwise go unutilized.

On the other side of the coin, all quantitative data is based on qualitative judgment. Numbers cannot be interpreted without understanding the assumptions which underlie them. For example, a simple 1-to-5 rating variable:
We can't really understand this quantitative value unless we dig into some of the judgments and assumptions that underlie it:
Did the respondent understand the term "capital punishment"?
Did the respondent understand that a "2" means that they are disagreeing with the statement?

Clearly, all numerical information involves numerous judgments about what the number means.

The bottom line is that quantitative and qualitative data are, at some level, virtually inseparable. Neither can be considered devoid of the other. To ask which is "better" or more "valid" ignores the intimate connection between the two.