Qualitative and quantitative research are the two main schools of research, and although they are often used in tandem, the benefits and disadvantages of each are hotly debated. Particularly in the social sciences, the merits of both qualitative and quantitative research are fought over, with intense views held on both sides of the argument. It is generally agreed upon, however, that there are some phases of research where one or the other is clearly more useful than the other, and so few people completely dismiss either.
Quantitative research is probably the least contentious of the two schools, as it is more closely aligned with what is viewed as the classical scientific paradigm. Quantitative research involves gathering data that is absolute, such as numerical data, so that it can be examined in as unbiased a manner as possible. There are many principles that go along with quantitative research, which help promote its supposed neutrality. Quantitative research generally comes later in a research project, once the scope of the project is well understood.
The main idea behind quantitative research is to be able to separate things easily so that they can be counted and modeled statistically, to remove factors that may distract from the intent of the research. A researcher generally has a very clear idea what is being measured before they start measuring it, and their study is set up with controls and a very clear blueprint. Tools used are intended to minimize any bias, so ideally are machines that collect information, and less ideally would be carefully randomized surveys. The result of quantitative research is a collection of numbers, which can be subjected to statistical analysis to come to results.
Remaining separate from the research emotionally is a key aspect of quantitative research, as is removing researcher bias. For things like astronomy or other hard sciences, this means that quantitative research has a very minimal amount of bias at all. For things like sociological data, this means that the majority of bias is hopefully limited to that introduced by the people being studied, which can be somewhat accounted for in models. Quantitative is ideal for testing hypotheses, and for hard sciences trying to answer specific questions.
Qualitative research, on the other hand, is a much more subjective form of research, in which the research allows themselves to introduce their own bias to help form a more complete picture. Qualitative research may be necessary in situations where it is unclear what exactly is being looked for in a study, so that the researcher needs to be able to determine what data is important and what isn’t. While quantitative research generally knows exactly what it’s looking for before the research begins, in qualitative research the focus of the study may become more apparent as time progresses.
Often the data presented from qualitative research will be much less concrete than pure numbers as data. Instead, qualitative research may yield stories, or pictures, or descriptions of feelings and emotions. The interpretations given by research subjects are given weight in qualitative research, so there is no seeking to limit their bias. At the same time, researchers tend to become more emotionally attached to qualitative research, and so their own bias may also play heavily into the results.
Within the social sciences, there are two opposing schools of thought. One holds that fields like sociology and psychology should attempt to be as rigorous and quantitative as possible, in order to yield results that can be more easily generalized, and in order to sustain the respect of the scientific community. Another holds that these fields benefit from qualitative research, as it allows for a richer study of a subject, and allows for information to be gathered that would otherwise be entirely missed by a quantitative approach. Although attempts have been made in recent years to find a stronger synthesis between the two, the debate rages on, with many social scientists falling sharply on one side or the other.