Interpretation of quantitative data

Interpretation of quantitative research data is an area in which a systematic method of approaching data and a great deal of common sense are the two most useful attributes. The first step is to go through all the tables one by one looking at the statistics. What do the descriptive statistics indicate about the characteristics of the market?

■ Frequencies, percentages, averages, dispersion?

■ When a difference is seen between two related statistics, is it a significant difference?

■ Older people from younger?

■ When there is no difference, is that significant?

■ If it is statistically different, will it matter anyway?

■ What relationships exist within the data using techniques of correlation and regression?

The purpose of the analysis is to uncover whatever is relevant and significant in the data; for instance, to isolate trends, tendencies or new factors in such things as competition, market structure, consumer habits or external variables. Interpretation should draw out implications of the data for management policy and action in the present and in the future. It should also highlight indicators based on this survey by which to monitor and assess the results of any action proposed. Interpretation of the data should also identify any weaknesses in the database and point these out if real assistance is to be given to the decision maker.

Within the marketing research industry there are two schools of thought about the interpretation of marketing research data. One school suggests that the role of the marketing researcher is simply to collect, analyse and report on the data without drawing interpretation for management policy or action. Only in this way can the researcher's objectivity be preserved and freedom be left for management to act on data as it sees fit. The other school of thought suggests that the researcher who has been involved in deciding what data is to be collected, with its collection and its subsequent analysis, will have developed ideas about the implications of the data for the decision to be made. Those ideas should be transmitted to the research user as recommendations. It is up to the research buyer to indicate at the outset whether or not he or she is looking for guidance on possible action as part of the interpretative process.

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