Processing Questionnaire Data

Having designed a questionnaire and administered it to an appropriate sample is half the battle. Now comes the final phase of our research, the processing of the data. The starting point of this phase is the very salient presence of stacks of completed questionnaires taking up what little empty space there is in our office. Accordingly, our initial priority is to get rid of these stacks and transform the information that is hidden in these piles of questionnaires into a more useful form that we can easily store, access, sort, and analyze (Brown, 2001).

"Many books seem to deal with programming for particular statistical analyses, but few detail the painful experience of going from a stack of disorganized hard copy to on-line data that are trustworthy."

Questionnaire data is most usable if it is stored in a computer file. This is a prerequisite to any professional analysis of the data but even if you are engaged in a small-scale investigation that is not intended to result in a research publication you can save a lot of time if you enter the data into a spreadsheet, for example. Modern computer programs tend to be so user-friendly that one can often learn to use them with less effort than what would be required, for example, to calculate the mean (i.e., the average) scores of the questionnaire responses manually, using a pocket calculator.

This chapter will describe the consecutive steps in processing questionnaire data. We will start with methods of scoring and coding the responses and then entering the data into a computer file. Following this, I will discuss the analysis of closed and open-ended items separately. The chapter will be concluded by summarizing the main types of computer software we can utilize for our research, the most important aspects of reporting questionnaire data, and finally the various ways we can complement our survey data with information obtained from other sources. It may be worth reiterating at this point that this chapter will not elaborate on statistical and qualitative techniques of data analysis. There are excellent books available that survey these procedures (see the 'Further reading' box at the beginning of Chapter 1).

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