1. SRM I answers

2. Project Report Expectations

3. Do yourself a favor Read the Course Manual Review the Grading Rubrics while writing your report Ask yourself “What will it take to get a 5?” Remember there are four serious but easily avoidable “fouls”; don’t give me a chance to penalize you Start early Come to me or Ashwini if you have problems

4. Expectations Acknowledge important limitations or confounds Grade is not dependent on statistical significance APA style – just adhere to it. APA style The ability to write well is a bonus Not sure how to write well? Read more Psychological Science articles s…l...o...w…l…y My mantra: Be clear, complete, and unambiguous.

5. Exam Tips

6. Tips Sleep 8 hours Don’t panic. Work through information calmly Draw diagrams; doodle; plan your answers Open book: For some questions, the answers can be found in the slides. But you need to revise them well so that you know where to find them! You are allowed to bring laptop (but no internet)

7. SRM II Grand Finale Week 12

8. SRM I Scientific method Descriptive statistics Inferential statistics Hypothesis testing T-test, chi-square, ANOVA, regression, correlation Power, effect size, confidence intervals

9. SRM II Questionnaire development Experimental research Control groups Single factor designs Factorial designs Small N, observational, correlational designs Quasi-experimental Lots of data analyses Lots of critiques about other people’s research Your first independent research project!

10. Q: “How much from SRM I will be in our exams?” A: If you have understood all concepts in SRM II, you have mastered the minimum basics of SRM I (e.g., mean, SD, F, p, inference). There will be no questions on regression, power, and confidence intervals in your SRM II exam

11. Questionnaire development What is a psychological construct? How do you operationalize it? How do you measure it? Validity – Predictive – Discriminant – Construct – Face Reliability – Internal consistency – Inter-rater (not covered)

12. Experimental research What is the defining characteristic of an experiment? Principles of causality (what are they?) Threats to internal validity – Biases (what kinds?) – Regression to the mean – History and maturation

13. Control problems Between/within-subjects designs each has its own control problems Creating equivalent groups (between-subj) Randomization and counterbalancing (within- subj) Cohort effects in longitudinal design

14. Control problems Just because the experimenter didn’t investigate factor B in a A  Y design, is A a confound? No! B could be a moderator (A*B  Y) What exactly is a confound? – A confound is an alternative explanation that you don’t want – A mediator is an explanation that you want – Both are explanatory variables. What does your theory say? What is worth controlling for?

15. Single factor designs Distinction between factors and levels Various control groups – Placebo – Waitlist – Yoked Nested models (you need to learn how to recognize it when you see one)

16. Factorial designs Reality is complex Having additional factors help us understand this complexity This complexity can reveal – The boundary conditions – The processes (water-faucet analogy) Fully between, fully within, mixed subjects

17. Quasi-experimental designs We went through examples of earthquake and epidemiological studies Well-controlled experiments may not always be possible Researchers sometimes need to be opportunistic too.

18. Small N, observational, correlational designs Small N is useful, though rarely used Lab-based studies can only capture a tiny part of what it means to be human Observational studies are a nice complement

19. Is there an SRM III? There are other designs out there: Observational, survey research methods, Big Data, etc. There are other statistics out there: Structural equation modeling, multilevel modeling, mediation, survival analysis, cluster analysis, logistic regression, trend analysis, etc. Want to learn more? Take Field Methods by Prof Valentina Zuin (I might teach in her course too, on field experiments.) No =( Yes =)

20. The world of possibilities.

21. BioCogDevClinicalSocial Statistics Research Methods

22. You have come a long way.

23. Some of you freaked out when you knew that statistics was compulsory.

24. You are here because you persevered.

25. Where do you go from here?

26. Insert curriculum chart

27. Where will you go from here? I don’t know. But I wish you well.