Questionnaire Design and Analysing the Data Using Spss

Topics: SPSS, Question, Pearson's chi-square test Pages: 11 (3423 words) Published: August 26, 2012
Questionnaire design and analysing the data using SPSS Questionnaire design.

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For each decision you make when designing a questionnaire there is likely to be a list of points for and against just as there is for deciding on a questionnaire as the data gathering vehicle in the first place. Before designing the questionnaire the initial driver for its design has to be the research question, what are you trying to find out. After that is established you can address the issues of how best to do it. An early decision will be to choose the method that your survey will be administered by, i.e. how it will you inflict it on your subjects. There are typically two underlying methods for conducting your survey; self-administered and interviewer administered. A self-administered survey is more adaptable in some respects, it can be written e.g. a paper questionnaire or sent by mail, email, or conducted electronically on the internet. Surveys administered by an interviewer can be done in person or over the phone, with the interviewer recording results on paper or directly onto a PC. Deciding on which is the best for you will depend upon your question and the target population. For example, if questions are personal then self-administered surveys can be a good choice. Self-administered surveys reduce the chance of bias sneaking in via the interviewer but at the expense of having the interviewer available to explain the questions. The hints and tips below about questionnaire design draw heavily on two excellent resources. SPSS Survey Tips, SPSS Inc (2008) and Guide to the Design of Questionnaires, The University of Leeds (1996). The format of your questions will affect the answers; Keep your questions short, less than twenty five words if possible. Keep questions understandable make sure the subject understands the terms used and importantly how the format of the questionnaire works (an already filled in example is often useful for this). Don't use “double negatives,” they can be confusing. Choose appropriate question formats so they are understandable to the person answering and that enable you to analyse the resultant data. Some questions can be easily answered with a simple single answer (e.g. do you smoke (y/n); what gender are you? (m/f), but others may require multiple choices a scale or, perhaps even a grid. Do make sure you know how to analyse the data you get, if you can't analyse the resulting data there was little point in collecting it. A research proposal should address analysis, a simple sentence "data will be analysed using SPSS" may pass the buck to SPSS but won't help much when you refer back to your plan. You should have an eye on the analysis when designing the questionnaire. Checking this is feasible should be part of the piloting; this will check that the data are arrangeable in the formats needed for analysis and that you have the resources to do it.

Questionnaire design and analysing the data using SPSS

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You might include open ended questions in the questionnaire, do though be aware that they will be "tainted" by the context of being in with strictly quantitative questions. The pilot is a good time to use more open questions to check there are sufficient options on multi choice answers and that there is sufficient discrimination in the questions, so not all the answers are the same when there is likely to be a range of views/responses. Ambiguous questions. Check for ambiguity in your questions, make sure what you're asking is obvious. Ambiguous questions not only yield no useful data but can frustrate the respondent and encourage them to give up! Avoid asking two questions at once. For example, “Are you happy with the amount and timeliness of feedback you receive from your tutors?” Analyzing the responses to such a question would be made practically impossible because you won’t be able to tell which part of the question the respondent was answering. Leading Questions. Leading questions...
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