Research Skills

1. Research Skills Week 3: Designing a questionnaire

2. Last Week • Decided on a subject area • Performed a literature search • Started to think about your research question and hypotheses • This week: Designing a questionnaire to test your hypotheses.

3. Today • Sampling • Consent • Question types • Answer types • Questionnaire design • Coding

4. Sampling • Who to ask: your target population • How many people: 20 (5 per group member) • Avoid a biased sample, e.g. if asking about drinking behaviour in men and women: • Don’t just ask women • Don’t just ask people in a bar • Don’t just ask tee-totallers

5. Consent • You must adhere to a strict code of ethics in your research: http://www.bps.org.uk/the-society/code-of-conduct/ • Participants must: • give consent to take part • not be coerced into participating • be free to withdraw at any time • Administering your questionnaires already has ethics approval.

6. Question Types: Open-Ended • Participants create their own answers • “What is your age?” • “Are you a smoker?” • “What are your favourite TV programmes?” • “How much do you like biscuits?” • To make data analysis easier DO NOT use open-ended questions that allow participants to write long responses

7. Question Types: Closed-Format • Experimenter provides participants with options • Choice of category:- Are you a smoker? Never smoked / Current smoker / Ex-smoker • Likert scale: - How strongly do you agree with the statement “I like biscuits” 1 2 3 4 5 Strongly Disagree Disagree Neutral Agree Strongly Agree • Checklists: Circle the TV programmes that you watch • Rating scales: How much do you like this drink, on a scale of 1-10? • Ranking: Order these sports in terms of how much you like them

8. Advantages and Disadvantages • Open-Ended • Exploratory • Useful when you can’t cover all the possible answers • Impractical in terms of analysis • Closed-Format • Easy and quick to fill in • Doesn’t matter how literate or articulate you are • Easy to code, record, and analyse results quantitatively • Easy to report results

9. Answer Types: Continuous Data • If the answer to the question is a number that represents an amount, e.g. • IQ score • Height • How long it takes to complete a jigsaw puzzle • Likert scale responses • Ranks • Top tip: Calculating a mean makes sense with continuous data (but not with categorical data)

10. Examples of Continuous Data • Please give an approximation of the number of alcoholic drinks you normally consume on a Saturday night: … Drinks. • Please indicate your agreement with the following statement: • I feel that I should drink less on a Saturday night □ □ □ □ □ 1 2 3 4 5 Strongly Disagree Neutral Agree Strongly Disagree Agree

11. Answer Types: Categorical Data • If the answer to the question is: • a word • “Yes” • a sentence • “I think that biscuits are tasty” • a description • “Physics student” • a code that represents a category • 1 = undergraduate, 2 = postgraduate • NB: Numerical codes can be used to represent categorical responses BUT this does not transform categorical data into continuous data.

12. ExamplesCategorical Data • In which town were you born? ……. • Please indicate your gender: □ Male □ Female • Which actor is the hunkiest? □ Brad Pitt □ Johnny Depp □ Orlando Bloom

13. Examples of Tricky Bits of Data • “Please indicate your age:” • Continuous: … Years • Categorical : □ 18-25 □ 26-30 □ 31–35 □ 36–40 etc. • Categorical : ... Years □ Older than 60 Years • “How many days a week do you usually exercise?” • Continuous : … days • Continuous : □ 1 day □ 2 days □ 3 days □ 4 days □ 5 days □ 6 days □ 7 days • Categorical : □ 1 day □ 2 days □ 3 days □ 4 days □ 5 days or more • This can be applied to a number of data

14. Questionnaire Design • Keep it short and simple • Start with an introduction/ welcome message • Allow not applicable responses to all possibly relevant questions • Say thank you to your participants

15. Questionnaire Design • Go from general to particular • Go from easy to difficult • Go from factual to abstract • Do not start with demographic and personal questions (put these at the end)

16. Questionnaire Design • Start with a title • Assure anonymity • Assign each questionnaire a number instead of asking for names • Avoid personal and sensitive questions • Be aware that you may bias answers simply by being there • Try to avoid biased wording • e.g. “Would you agree that the death penalty is a bad idea?”

17. Coding • Giving numbers to categories in categorical data is called coding • e.g. “Yes” becomes 1 and “No” becomes 2 • Codes can be allocated either before the question is answered (pre-coding) or afterwards (post-coding) • You should agree on codes with the rest of your group before you enter any data • We will come back to this in Week 5

18. Plan of action • Think about your sample • Create your questionnaire • Pre-test the questionnaire (if practical) • Conduct interviews • Enter data • Analyse the data • Write your research proposal • Write your lab report

19. Hypotheses • 2 Categorical Hypotheses: - • Should be tested with 2 categoricalquestions • e.g. “Men prefer to buy fast food at Burger King, while women prefer to buy fast food at McDonalds” • 2 Continuous Hypotheses: - • Should be tested with a categoricalquestion and a continuousquestion • e.g. “Males consume a larger quantity of alcoholic beverages per week than females”

20. By the time you leave class • Put together your group questionnaire • 10 questions in total • 5 Categorical questions • 5 Continuous questions • Try to consider your hypotheses while creating the questions • Get a tutor to check it over

21. By next week • Try to have asked 20 people to fill out your questionnaire • Top tip: If psychology students are a suitable sample, swap questionnaires with each other