Whereas quantitative research emphasizes the study of factors that can be explicitly measured, qualitative data is more descriptive. This has a couple of key implications. The first is that qualitative data is inherently more subjective. It is directly subject to interpretation from the researcher. Quantitative data can be interpreted by the researcher, but ultimately the data is presented in raw form and can therefore be interpreted by another researcher as well. The other implication is that whereas qualitative data is interpreted at the observation level, quantitative must be analyzed at the root level. The way in which is survey is designed will reveal the biases of the researcher, so that is the level that must be given the most scrutiny. Beyond this, quantitative research often reflects the use of proxies, so there is some distance between the numbers generated and the actual phenomenon being studies. This especially true of business, where for example the number of takeovers is used as a quantitative proxy for the qualitative element of corporate governance. The researcher must be aware of the imperfections of the proxy; with qualitative data it is more the interpretation that must be subject to scrutiny than the researcher design itself.
5. Data from qualitative research is substantially different from data from quantitative research....
Superficially, qualitative research consists of descriptors that are non-numeric. Quantitative research is based strictly around numeric measures. The result of this is that the two must be interpreted entirely differently. The data is also acquired in a different manner as well. Qualitative measures are often gathered through direct observation, while quantitative results can often be derived through primary sources other than observation (annual reports in business, for example). The method of gathering the data may not differ, but the degree to which the data is objective and the degree of subjective interpretation of the data will differ between qualitative and quantitative data.
6. This qualitative research would be relatively straightforward. The first step would be to determine the models and colors that needed to be tested. The second step would be to determine the necessary sample size. For a qualitative study, the qualitative measures would need to be determined -- for example, "like," "do not like," etc. These measures could also be adapted to quantitative measures. Once the measures are set, the designs and colors should also include domestic examples as well, so that the company can understand consumer response to the new designs and colors relative to the models and colors already available in the domestic U.S.…
