Basic Methodologies

1. Basic Methodologies Psych 231: Research Methods in Psychology

2. Organizes, Explains, & Accounts for the data • If there are data relevant to your theory, that your theory can’t account for, then your theory is wrong • Either adapt the theory to account for the new data • Develop a new theory that incorporates the new data Properties of a good theory

3. Exclusive usage of one or the other can be problematic • Typically good research programs use both “Data driven research” reasoning from the data to the general theory Theory Deduction Induction “Theory driven research” reasoning from a general theory to the data Data The chicken or the egg?

4. “No amount of experimentation can ever prove me right; a single experiment can prove me wrong.” • Organizes, Explains, & Accounts for the data • Testable/Falsifiable – can’t prove a theory, can only reject it Properties of a good theory

5. EXTINCTION OF THE DINOSAURS FULLY EXPLAINED • Beware theories that are so powerful/general/flexible that they can account for everything. These are not testable Omnipotent Theory

6. Beware theories that are so powerful/general/flexible that they can account for everything. These are not testable • Karl Popper claimed that Freudian theory isn’t falsifiable • If display behavior that clearly has sexual or aggressive motivation, then it is taken as proof of the presence of the Id • If such behavior isn’t displayed, then you have a “reaction formation” against it. So the Id is there, you just can’t see evidence of it. • So, as stated, the theory is too powerful and can’t be tested and so it isn’t useful Omnipotent Theory

7. Organizes, Explains, & Accounts for the data • Testable/Falsifiable • Generalizable – not too restrictive • The theory should be broad enough to be of use, the more data that it can account for the better • The line between generalizability and falsifiability is a fuzzy one. Properties of a good theory

8. Organizes, Explains, & Accounts for the data • Testable/Falsifiable • Generalizable • Parsimony (Occam’s razor) • For two or more theories that can account for the same data, the simplest theory is the favored one “Everything should be made as simple as possible, but not any simpler.” Properties of a good theory

9. Organizes, Explains, & Accounts for the data • Testable/Falsifiable • Generalizable • Parsimony • Makes predictions, generates new knowledge • A good theory will account for the data, but also make predictions about things that the theory wasn’t explicitly designed to account for Properties of a good theory

10. Organizes, Explains, & Accounts for the data • Testable/Falsifiable • Generalizable • Parsimony • Makes predictions, generates new knowledge • Precision • Makes quantifiable predictions Properties of a good theory

11. Claim:People perform best with 8 hours of sleep a night. • How might we go about trying to test this claim? • How should we test it (what methods)? • What are the things (variables) of interest? • What is the hypothesized relationship between these variables? Today’s focus Conducting Research: An example

12. Descriptive: • Observational • Survey • Case studies • Correlational • Experimental General research approaches

13. The researcher observes and systematically records the behavior of individuals • Naturalistic observation • Participant observation • Contrived observation Observational methods

14. Observation and description of behaviors within a natural setting • Can be difficult to do well • Good for behaviors that don’t occur (as well) in more controlled settings • Often a first step in the research project Naturalistic Observation

15. The researcher engages in the same behaviors as those being observed • May allow observation of behaviors not normally accessible to outside observation • Internal perspective from direct participation • But could lead to loss of objectivity • Potential for contamination by observer Participant Observation

16. The observer sets up the situation that is observed • Observations of one or more specific variables made in a precisely defined setting • Much less global than naturalistic observations • Often takes less time • However, since it isn’t a natural setting, the behavior may be changed Contrived observation

17. Advantages • May see patterns of behaviors that are very complex and realized on in particular settings • Often very useful when little is known about the subject of study • May learn about something that never would have thought of looking at in an experiment Observational methods

18. Disadvantages • Causality is a problem • Threats to internal validity because of lack of control • Every confound is a threat • Lots of alternative explanations • Directionality of the relationship isn’t known • Sometimes the results are not reproducible Observational methods

19. Widely used methodology • More detail in Week 11 • Can collect a lot of data • Done correctly, can be a very difficult method • Doesn’t provide clear cause-effect patterns Survey methods

20. This view has a number of disadvantages • There may be poor generalizabilty • There are typically a number of possible confounds and alternative explanations • Intensive study of a single person, a very traditional method • Typically an interesting (and often rare) case • Phineas Gage • Sept 13, 1848 Explosion propelled a railroad tamping rod through his brain Case Histories

21. Measure two (or more) variables for each individual to see if the variables are related • Used for: • Predictions • Reliability and Validity • Evaluating theories • Problems: Can’t make casual claims Correlational Methods

22. We’d like to say: • (variable X) causes (variable Y) • To be able to do this: • The causal variable must come first • There must be co-variation between the two variables • Need to eliminate plausible alternative explanations Causal claims

23. One might argue that turbulence cause coffee spills One might argue that spilling coffee causes turbulence • Directionality Problem: • Airplanes and coffee spills Causal claims

24. Happy people sleep well • Or is it that sleeping well when you’re happy? • Third variable problem: • Do Storks bring babies? • A study reported a strong positive correlation between number of babies and stork sightings • Directionality Problem: • Airplanes and coffee spills Causal claims

25. Theory 1: Storks deliver babies

26. Theory 2: underlying third variable

27. Manipulating and controlling variables in laboratory experiments • Must have a comparison • At least two groups (often more) that get compared • One groups serves as a control for the other group • Variables • Independent variable - the variable that is manipulated • Dependent variable - the variable that is measured • Control variables - held constant for all participants in the experiment The experimental method

28. Advantages • Precise control possible • Precise measurement possible • Theory testing possible • Can make causal claims The experimental method

29. Disadvantages • Artificial situations may restrict generalization to “real world” • Complex behaviors may be difficult to measure The experimental method

30. Ethics in research • Read GF chapter 4 (note syllabus said chpt 3) Next time