i. Research Overview lecture of psy.pptx

Research methods of psychology

1. Research Overview Research Basics

2. Steps in the Research Process Develop research Idea Search literature & develop hypothesis Select a research design & method Nonexperimental or experimental Manipulations and measurement Sampling and recruitment plan Conduct study Evaluate data Report results Refine/Retest

3. Designing a Study Which strategy, design, and/or method should be used to test the hypothesis? Decision based on many factors Advantages & limitations of the strategy/design/method State of current knowledge on topic Practical issues – money, time, resources Ethical issues

4. Strategy , Design, & Method Research Strategy G eneral approach to research determined by the kind of question posed by the researcher Nonexperimental, Quasi-experimental or Experimental? Research Design P lan for implementing research strategy Groups versus individuals Same individuals versus different individuals Number of variables manipulated and measured Research Method How are the data being collected?

5. Research Strategies G eneral approach and goals of a study Nonexperimental Descriptive or Single-variable Predictive Quasi-Experimental Experimental Can be some gray area S ometimes a strategy is linked to a method Sometimes a study is somewhere in between two strategies A single study may have multiple hypotheses, use more than one research strategy, and also use different methods.

6. Descriptive or Single Variable Research Merely describes a variable or variables Not able to say anything about whether variables are related nor make cause-effect statements

7. Predictive Correlational Investigates relations between 2 or more variables Not explaining the relationship (no causal assignment) Identifying patterns in data Direction Strength Form Could have collected the data through a survey, observation, from existing records (i.e., archival), etc.

8. Correlational 1. Direction of relationship Positive, Negative, or No relationship Positive No relation Negative 8 SAME DIRECTION OPPOSITE DIRECTION

9. Correlational 2 . Strength of relationship Correlation coefficient Ranges from -1.00 to +1.00 -1.00 reflects a perfect negative relationship +1.00 reflects a perfect positive relationship Closer to zero reflects a weaker relationship Strongest Relationship

10. Correlational 3 . Form of relationship Linear relation Change is fairly constant C urvilinear relation Change is not constantly the same

11. Guess the Direction & Size of Relation Positive Strong Negative Perfect Negative Weak No Relation

12. Correlational Longitudinal Current measure Thought to be the cause Longitudinal Future measure Thought to be the effect Predictor Variable  X-axis Criterion Variable  Y-axis Sometimes also called the DV or the outcome variable

13. Correlation does not imply causation Alternative Explanations Directionality problem Third-variable problem Lurking variables, third variables, confounds Time spent playing violent videogame Aggressive behavior Aggression Parental Monitoring Violent videogames

14. Quasi-experimental Attempts to answer cause-effect questions However, includes a flaw that prevents this Usually examining pre-existing variables (i.e., characteristics about participants that can’t be manipulated) or participants self-select themselves into groups I.e., “Subject”, “Participant” “Quasi-independent” E.g., gender, smoking status

15. Explanatory Experimental Research Determine one variables cause changes in another variable Involves manipulation of variables, random assignment, & control Independent Variable (IV) – manipulated Randomly assigned to levels/conditions of the IV Random assignment is a procedure used to eliminate participant variables as alternative explanations Dependent Variable (DV) – measured Hold all other variables constant Variable X (Cause) Variable Y (Effect)

16. Other interpretations??? 16 Incidental (extraneous) variables Other variables that are not the focus Confound variables Vary reliably with the manipulated variable Serve as an alternative explanation Sometimes referred to as “third-variables” or “lurking variables”

17. More on Independent Variables Does 1 IV have an effect on the DV? The terms – levels, conditions – have similar meaning. Interaction effects (e.g., Factorial Designs) Do IVs interact to influence a DV? The terms – levels, conditions – now have different meanings. Levels refer to the different amounts of each IV. Conditions refer to the different combinations of the levels of the IVs.

18. Example Task Difficulty (A) Easy (A 1 ) Difficult (A 2 ) Presence of others (B) Alone (B 1 ) Easy task alone Difficult task alone Audience (B 2 ) East task w/ audience Difficult task w/ audience This study has two independent variables (IV) (IV) Presence of others 2 levels: Alone vs. Audience (IV) Task difficulty 2 levels: Easy vs. Difficult 4 conditions

19. Think this through … Explain why we cannot make causal claims with correlational data. Be specific. Explain why we can make causal claims with experimental data (assuming well-designed study). Be specific.

20. Explain why we cannot make causal claims with correlational data. Explain why we can make causal claims with experimental data (assuming well-designed study ). What’s the difference between levels and conditions? If I said that the correlation between anxiety and depression was .75, how would you interpret this correlation coefficient? Mini-Review