The researcher’s goal is to organize a large quantity of specific details into a coherent picture, model, or set of interlocked concepts.
A qualitative researcher rarely tries to document universal laws; rather, he or she divides explanations into two categories: highly unlikely and plausible. The researcher is satisfied by building a case or supplying supportive evidence. He or she may eliminate some theoretical explanations from consideration while increasing the plausibility of other because only a few explanation will be consistent with a pattern in the data. Qualitative analysis can eliminate an explanation by shoeing that a wide array of evidence contradicts it. The data might support more than one explanation, but all explanations will not be consistent with it. In addition to eliminating less plausible explanations, qualitative data analysis helps to verify a sequence of events or the steps of a process. This temporal ordering is the basis of finding associations among variables, and it is useful in supporting causal arguments.