1. 1 Lecture – Week 5 - Questionnaire Design & Selecting a Stats Test & Intro to G-Power. First - Some tidying Up According to my records there are a few individuals who have not yet obtained Supervisors !!! Reminder: ethics form and proposal must be submitted together.

2. 2 Summary Some aspects of Questionnaire Design How to select a statistical test Calculating Sample Size - Brief intro to the G*Power interface – software for calculating sample size (amongst other things). Freely available at: http://www.psycho.uni-duesseldorf.de/abteilungen/aap/gpower3/ You need to know (or estimate) at least 3(+) things before you can calculate sample size: alpha Power Effect size + some elements of the research design

3. 3 Why calculate Sample Size ? The likelihood of obtaining a statistical significant result is in (large) part a function of the sample size – the larger the sample size the greater the likelihood of obtaining a significant result. It would be unethical to ask a number of individuals to take part in a study or experiment where there is little or no chance of obtaining a significant result with that sample size. You would be wasting your time and perhaps more importantly the respondents time - at the very least!

4. 4 You need to know (or estimate) at least 3(+) things before you can calculate sample size: alpha – this is the “level of significance” used in the study (convention 0.05) Power – this is the ability of a statistical test to reject a false null hypothesis – the larger the power the bigger the sample required (Not committing a type II error: convention 0.8) Effect size – this is the ‘strength of difference’ or ‘strength of association’ likely to be apparent in the population – the larger the effect size the smaller the sample required (can be obtained from previous research or a minimum meaningful effect – see conventions on later slide) + some elements of the research design (e.g. how many levels of the independent variable (conditions) or how many predictors in the study)

5. 5 Rules of thumb for effect sizes for different statistical tests/distributions Test Effect Size ‘Small’‘Medium’‘Large’ t-test0.20.50.8 F test0.10.250.4 Correlation0.10.30.5 X 2 0.10.30.5 Multiple regression 0.020.150.35

6. 6 http://web.psych.washington.edu/writingcenter/writingguides/pdf/stats.pdf http://www.ilstu.edu/~mshesso/apa_stats_format.html http://www.muhlenberg.edu/depts/psychology/APA.pdf Some website resources for writing style (there may be more).