1. Using the scientific method Observational Methods Psych 231: Research Methods in Psychology

2. Announcements Remember Monday is Labor Day, no classes that day ReggieNet Quizzes They are all posted for the semester. It is your responsibility to be aware of the due dates. Quiz 2 (chapters 2&3) is Due Tonight at midnight, Aug. 27 This week’s labs - Library Labs: Milner rooms 213C (for the psycINFO lecture) Next week’s labs: Download and read the Assefi & Garry (2003) article before labs

3. Conducting Research: An example Claim: People perform best with a good night of sleep. To begin to answer the claim we’ve got to FOCUS the idea Break the general idea down into smaller more specific ideas Develop theories as to how & why EVALUATE the idea (e.g., the ROT test) TEST the idea: using research methods to test parts of the theories (hypotheses) Sleep walking story (2)Sleep walking story2 Sleep and high school (2)Sleep and high school2 Science of sleep

4. Conducting Research: An example Claim: People perform best with a good night of sleep. Focusing the idea What do we mean by “perform best”? Academic performance? Physical performance? What do we mean by “good night sleep”? 8 hrs?, Uninterrupted?, 2 hours of REM?REM What is the underlying theory? What hypotheses do we test? e.g., Consolidation of memories happen during REM sleep, so getting more REM sleep should lead to better recall Operational definitions

5. Conducting Research: An example Claim: People perform best with a good night of sleep. Evaluating the idea (ROT) Can we replicate the research, do we get similar results? Answer may depend on how you choose to make your observations (your research methods) How do we observe performance? How do we observe good sleep? Recall tests, recognition tests, “brain waves,”,,, Are our predictions testable?

6. Conducting Research: An example Claim: People perform best with a good night of sleep. How might we go about trying to test this claim? What are the things (variables) of interest? What is the hypothesized relationship between these variables? How should we test it? How do we observe the behavior? What research design should we use, what are our goals?

7. Observational approaches: Data collection How do we observe the behaviors of interest? Types of research designs What kinds of research questions are you investigating? E.g., Cause and effect? Descriptive? Conducting Research

8. Observational Methods Observational approaches: Data collection How do we observe the behaviors of interest? Naturalistic observation Participant observation Survey & interviews Archival data Systematic (contrived) observation Experiments Observation without manipulation Direct Observation

9. Observational Methods Naturalistic Observation: Observation and description of behaviors within a natural setting Jane Goodall Dian Fossey High external validityexternal validity Good for behaviors that don’t occur (as well) in more controlled settings Often a first step in the research project Can be difficult to do well Hard not to influence things (reactivity effect) Takes a long time Need multiple observers to agree

10. Observational Methods Participant Observation: The researcher engages in the same behaviors as those being observed Participant Observation 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 http://www.sil.org/~headlandt/students.htm

11. Observational Methods Survey methods: Questionnaires and interviews that ask people to provide information about themselves Widely used methodology Best way to collect some kinds of information: Descriptive, behavioral, and preferential e.g., demographic information, recreational behavior, and attitudes Large amounts of data can be collected quickly with relatively little cost (effort, time, etc.) But they’re often not as “cheap” as you may think Done correctly, can be a very difficult method

12. Archival data: Rather than making direct observations, researcher examines existing public or private records If the appropriate existing records can be found, no need for data collection Data set may be more extensive than what you could collect yourself However, you are limited to the data that exists, may be no way to collect follow-up data Data may be of observations that you cannot (ethically) collect or manipulate E.g., murder rates, who marries whom, etc. Word of caution: be aware of how and where the data were collected Observational Methods

13. Observation without manipulation Advantages Complex patterns of behavior in particular settings Useful when little is known about the subject of study May learn about something that never would have thought of looking at experimentally 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

14. Systematic (Contrived Observation): 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

15. Types of research designs Case studies Intensive study of a small set of individuals and their behaviors Correlational Looking for a co-occurrence relationship between two (or more) variables Quasi-experimental Experimental designs with one or more non-random variables Experimental Investigating the cause-and-effect relationship between two (or more) variables through the manipulation of variables

16. Case Histories This view has some 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: Descriptive (and non-experimental). Interesting (and often rare) case. Fits well with clinical work. Phineas Gage (Sci. Am. Show) Phineas GageSci. Am. Show Sept 13, 1848 Explosion propelled a railroad tamping rod through his brain Changed personality See: Oliver Sacks’ books for some other great examplesOliver Sacks interview

17. Correlational Methods Measure two (or more) variables for each individual and see if the variables co-occur (suggesting that they are related) Used for: Predictions Establishing Reliability and ValidityReliability Validity Evaluating theories Limitation: Shouldn’t make casual claims ? or

18. Causal claims We’d like to say: To be able to do this:  There must be co-variation between the two variables  The causal variable must come first  Directionality problem Happy people sleep well Or is it that sleeping well when you are happy?  Need to eliminate plausible alternative explanations  Third variable problem Do Storks bring babies? Neyman (1952) reported a strong positive correlation between number of babies and stork sightings causes or

19. Causal claims r = 0.63 Source: Kronmal (1993) Do Storks bring babies? Neyman (1952) reported a strong positive correlation between number of babies and stork sightings

20. Theory 1: Storks deliver babies Is killing storks and effective method of controlling birth rates?

21. Theory 2: Underlying third variable

22. The experimental method 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 Allows for the testing of causal hypotheses Dependent variable - the variable that is measured Control variables - held constant for all participants in the experiment

23. The experimental method Advantages Precise control possible Precise measurement possible Theory testing possible Can make causal claims Disadvantages Artificial situations may restrict generalization to “real world” Complex behaviors may be difficult to measure Manipulating and controlling variables in laboratory experiments