1. Talks & Statistics (wrapping up) Psych 231: Research Methods in Psychology

2. Announcements Class experiment final draft papers due today Please make sure that your GA’s name is on it

3. Your posters (our checklist) Content Introduction Problem of interest Very brief summary of past research Basic purpose of experiment(s) Hypotheses Method Brief but clear Design Materials Procedure (brief) Results Descriptive statistics Inferential results Tables and figures Useful info to reader Easy to understand Discussion Hypothesis rejected or supported Implication of results A few take home points References

4. Your posters (our checklist) Format Overall clarity Organization Font size Figure/text balance Title Authors

5. Different kinds of talks Research Presentations (typically 10 to 30 mins) Paper with respondent Panel Presentation Workshop

6. Talk Content Create a logical progression to the talk Hourglass shape Work on the transitions between slides Be brief, but include enough details so that the audience can follow the arguments Use slides to help simplify/clarify points Include tables, graphs, pictures, etc. Don’t just read the slides but do “walk through” those that need it (e.g. graphs of results) Be careful of jargon, explain terms (if in fact you really need them)

7. Presentation of the talk Make it smooth (lots of practice will help) Watch your speaking rate (again, practice) Maintain eye contact with whole audience Emphasize the key points, make sure that the audience can identify these Point to the slides if it helps Beware jokes, can be a double-edged sword Don’t go over your time

8. Dealing with questions Repeat the question in your own words so that the rest of the audience can hear it to make sure that you understood the question to buy yourself some time to think about the answer Try not to be nervous you know your study better than anyone else When preparing, try to think of likely questions and prepare answers

9. Checklist for the talk Preparation Analyze the audience Choose your main points etc. Prepare the Final Outline fix any problems/loose ends Construct your “speaking” outline e.g., the note cards that you’ll read Rehearse, rehearse, rehearse

10. Some inferential statistical tests 1 factor with two groups T-tests Between groups: 2-independent samples Within groups: Repeated measures samples (matched, related) 1 factor with more than two groups Analysis of Variance (ANOVA) (either between groups or repeated measures) Multi-factorial Factorial ANOVA

11. Some inferential statistical tests 1 factor with two groups T-tests Between groups: 2-independent samples Within groups: Repeated measures samples (matched, related) 1 factor with more than two groups Analysis of Variance (ANOVA) (either between groups or repeated measures) Multi-factorial Factorial ANOVA

12. Analysis of Variance More than two groups Now we can’t just compute a simple difference score since there are more than one difference So we use variance instead of simply the difference Variance is essentially an average difference Observed variance Variance from chance F-ratio = Lot’s of degree’s of freedom to keep track of Overall df, df for numerator, df for denominator

13. 1 factor ANOVA 1 Factor, with more than two levels Now we can’t just compute a simple difference score since there are more than one difference A - B, B - C, & A - C XBXB XAXA XCXC

14. 1 factor ANOVA Null hypothesis: H 0 : all the groups are equal X A = X B = X C Alternative hypotheses H A : not all the groups are equal X A ≠ X B ≠ X C X A ≠ X B = X C X A = X B ≠ X C X A = X C ≠ X B The ANOVA tests this one!! Do further tests to pick between these XBXB XAXA XCXC

15. 1 factor ANOVA Planned contrasts and post-hoc tests: - Further tests used to rule out the different Alternative hypotheses X A ≠ X B ≠ X C X A ≠ X B = X C X A = X B ≠ X C X A = X C ≠ X B Test 1: A ≠ B Test 2: A ≠ C Test 3: B = C

16. Reporting your results The observed differences Kind of test Computed F-ratio Degrees of freedom for the test The “p-value” of the test Any post-hoc or planned comparison results “The mean score of Group A was 12, Group B was 25, and Group C was 27. A 1-way ANOVA was conducted and the results yielded a significant difference, F(2,25) = 5.67, p < 0.05. Post hoc tests revealed that the differences between groups A and B and A and C were statistically reliable (respectively t(1) = 5.67, p < 0.05 & t(1) = 6.02, p <0.05). Groups B and C did not differ significantly from one another” 1 factor ANOVA

17. Factorial ANOVAs We covered much of this in our experimental design lecture More than one factor Factors may be within or between Overall design may be entirely within, entirely between, or mixed Many F-ratios may be computed An F-ratio is computed to test the main effect of each factor An F-ratio is computed to test each of the potential interactions between the factors

18. Factorial ANOVAs Reporting your results The observed differences Because there may be a lot of these, may present them in a table instead of directly in the text Kind of design e.g. “2 x 2 completely between factorial design” Computed F-ratios May see separate paragraphs for each factor, and for interactions Degrees of freedom for the test Each F-ratio will have its own set of df’s The “p-value” of the test May want to just say “all tests were tested with an alpha level of 0.05” Any post-hoc or planned comparison results Typically only the theoretically interesting comparisons are presented