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Surveys, Questionnaire Design and Data Analysis.

Aims and Objectives. To understand the theory regarding sampling, and inferences to populationsTo evaluate the pros and cons of administration methodsWording of Questions and benchmarkingDetermining cause and effectAnalysing the survey dataTo consider the implications of these findings for your own research plans..

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Surveys, Questionnaire Design and Data Analysis.

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    1. Surveys, Questionnaire Design and Data Analysis. Dr Brendan Burchell Faculty of Social and Political Sciences Bb101@cam.ac.uk Wednesday 26th March 2008

    2. Aims and Objectives To understand the theory regarding sampling, and inferences to populations To evaluate the pros and cons of administration methods Wording of Questions and benchmarking Determining cause and effect Analysing the survey data To consider the implications of these findings for your own research plans.

    3. Sampling Theory As random samples increase in size, their properties resemble the population from which they are drawn more closely. SE of sample mean = SD / SQRT N Note Only applies to random samples. Sample size cannot combat bias. Size of population unimportant.

    4. Methods of Administration Face-to-face Time-consuming, costly? Worse social desirability biases? Post Low response rate Phone Who are you talking to? Internet? Improving.

    5. Is representative sampling Important? To make exact predictions about the nature of the population (e.g. to predict an election) Essential To explore the relationships between variables in a sample and generalise to a population Desirable To explore mechanisms, processes, qualitatively ?

    6. Methods of selecting random samples 1 Random number tables to select from populations 2 Random numbers and constant intervals (full list of population necessary) 3 Random numbers and procedures to infill gaps in population lists Stratified Samples (boosting small groups?)

    7. Multi-Stage Sampling Eg. sampling to select organisations, then workplaces, then individuals Weighting may be necessary to re-adjust sample to be representative of population

    8. Other Sampling Methods Telephone “random digits” Administrative lists Emails / Web Newspaper adverts Snowballing Theoretical Case-Studies Outliers

    9. Non-Response Reduced Sample Size Increased Error Costly, but no loss of representativeness Increased Bias Much more serious

    10. Reducing Non-Response Appropriate methods of administration E.g. face-to-face interviews Call-Backs Quality of postal questionnaire / covering letter Prizes / Rewards Relevance of topic

    11. Question Wording Open Ended What are the significant threats to Health and Safety involved in this process?________________ Closed Questions Which of the following are significant threats to the Health and Safety of this process? Human error, malfunction, fire, alcohol, inadequate training, operators falling asleep, earthquake, terrorism, faulty materials, employee sabotage, inadequate supervision, poor management, extreme weather, acts of god, computer errors, computer viruses, ……

    12. What are you trying to find out? “Objective facts”. How many days of manufacturing were lost last year due to equipment failure? Who knows? Can the results be verified? Perceptions How satisfied are you with the reliability of your equipment?

    13. Open vs closed questions Open Not constraining Need less piloting Get information “in their own words” Closed Less time-consuming to code Can include “other, please specify” Easier to lead?

    14. Overcoming Social Desirability When did you last do a health and safety check? We all know that if you completed health and safety checks as often as the rulebook says you should, you wouldn’t get anything else done. When did you last manage to do a health and safety check?

    15. Pilot all questions Spot the error: Do you work part time? Qualitative pilots? Quantitative pilots?

    16. Who is the expert? You or the Participant? How long have you been doing this job? How many errors have you made in the last month? OR Doing your job, does the number of errors you make decrease over time?

    17. Resources Plagiarism of questions is a virtue! See the Questionbank http://qb.soc.surrey.ac.uk/

    18. Analysing the data from a survey Specialist packages, eg Minitab, SPSS Or Generic tools, eg MS Excel Analyse the data in stages: Look at questions individually, check for coding errors, initial conclusions. Graph data. Start to look for evidence of differences between batches (i.e. relationships) by comparing means Only then, perhaps, check for statistical significance.

    19. Guiding Philosophies of Data Analysis Are you a Judge & Jury or a detective? Explore all aspects of data Not just Central Tendancy Mean, Median, Mode But Also Spread Shape Outliers

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