Discuss how the researcher should go about selecting a data analysis strategy (Figure 14.5 in the text)

What will be an ideal response?

The selection of a data analysis strategy should be based on the earlier steps of the marketing research process, known characteristics of the data, properties of statistical techniques, and the background and philosophy of the researcher.

The selection of a data analysis strategy must begin with a consideration of the earlier steps in the process: problem definition (Step I), development of an approach (Step II), and research design (Step III). The preliminary plan of data analysis prepared as part of the research design should be used as a springboard.

Changes may be necessary in light of additional information generated in subsequent stages of the research process. The next step is to consider the known characteristics of the data. The measurement scales used exert a strong influence on the choice of statistical techniques and, the research design may favor certain techniques.

It is also important to take into account the properties of the statistical techniques, particularly their purpose and underlying assumptions. Some statistical techniques are appropriate for examining differences in variables, others for assessing the magnitudes of the relationships between variables, and others for making predictions. The techniques also involve different assumptions, and some techniques can withstand violations of the underlying assumptions better than others.

Finally, the researcher's background and philosophy affect the choice of a data analysis strategy. The experienced, statistically trained researcher will employ a range of techniques, including advanced statistical methods. Researchers differ in their willingness to make assumptions about the variables and their underlying populations. Researchers who are conservative about making assumptions will limit their choice of techniques to distribution-free methods.