In fact, some qualitative data analysis strategies devote more effort to contextualizing than to abstracting or generalizing. This is based on the position that scientific knowledge is not found only in abstracting and generalizing; such knowledge can also derive from a deep and full description of a context. In other words, some qualitative research focuses on idiographic explanations rather than nomothetic ones (refer to pages 34-36 in Chapter 2 on different types of explanations). A third difference is that qualitative research tends to place more emphasis on inductive reasoning than on deductive reasoning. As we will see, qualitative researchers stress the value of letting concepts and abstract ideas emerge from the data rather than using the data to provide evidence for preexisting concepts and theories.
As a part of the goal of stressing the contextual, qualitative research maintain a close, interactive link between data collection and data analysis. In Chapter 1, we presented the stages in the research process as a sequence in which one is begun. In particular, we suggested that the data collection stage is completed before the data analysis stage begins and that data analysis is largely finished before conclusions are drawn. This is the way many quantitative and positivist researchers would describe the process. One major reason for this sequencing is to ensure that the data-collection procedures used are the same over time; if the measurement procedures change from the beginning to the end of the data collection phase, then you may be measuring different variables. This is an important consideration in research where there are clearly stated and quantifiable variables and hypotheses and quantitative measurement procedures are used.