Understanding the Scientific Method in Behavioral Sciences

1. Chapter 2 Methodology in the Behavioral Sciences

2. What is Science? • Knowledge based on observation and experimentation and validated by other scientists • Often (not always) uses an experiment to gain knowledge • Experiment: a test or trial to discover a cause-effect relationship

3. The Scientific Method • A method for attaining knowledge based on observation and experimentation • attempt to find empirical answers

4. Psychology as a Science:Levels of Analysis

5. Psychology as a Science:Levels of Analysis • “Hard” vs. “Soft” science • molecular vs. molar levels • few vs. many antecedent conditions • relatively simple vs. relatively complex systems • Reductionism • explanation in terms of more molecular analysis

6. Can science “prove” anything? • Which is a better explanation: molecular level or molar level? • Can science find “truth”? • any conclusion based on probabilistic reasoning • Scientific Method is self-correcting • use of programmatic research provides many partial answers to questions

7. Four Goals of Psychology

8. The Experimental Method 1. Questioning behavior 2. Generating a hypothesis 3. Designing the experiment 4. Conducting the experiment 5. Analyzing the results 6. Validating the experiment 7. Publishing the results

9. Questioning Behavior • Generating a research question • based on observation, intuition and training • research training includes knowledge of background information and previous conclusions • what part of the question needs to be solved?

10. Generating a Hypothesis • Hypothesis • a hunch, idea or theory that can be formally tested in an experiment • making predictions about outcome of an experiment • Operational Definition • defining something in terms of how it is measured • makes a theoretical question empirical

11. Designing the Experiment • Experiment tests the hypothesis • Independent Variable • the variable that is manipulated by the experimenter • Dependent Variable • the variable that is measured - influenced by the independent variable

12. Designing the Experiment • Experimental Subjects • receive the manipulation • Control Group(s) • does not receive the manipulation

13. Designing the Experiment • Within-subjects design • the response of each subject before and after the manipulation of the independent variable is compared • all subjects receive the manipulation • Between-subjects design • experimental group receives the manipulation • compared with a control group that receives no manipulation

14. Conducting the Experiment • Appropriate control must be maintained to ensure that data represent the original design • Want to avoid confounding variables • unknown or unidentified variable that causes the effect presumed to be caused by the independent variable

15. Analyzing the Results • Data can be presented in graphs • Look for Functional Relationship • orderly relationship between the independent variable and the dependent variable

16. Analyzing the Results:Statistical Tests • Begin with an assumption that the Null Hypothesis is correct • No differences exist between groups • Using statistics, can reject or accept the null hypothesis • based on the probability that differences would have occurred by chance anyway • Statistics cannot provide conclusions

17. Validating the Experiment • Scientific results are peer-reviewed • reviewed by other scientists - often anonymously • assumes validation by consensus

18. Publishing the Results • Following peer-review, results are published • provides information for other scientists to generate new experiments • open publication allows others to replicate and extend the original findings

19. Non-experimentalResearch Methods • Individual differences • can be assessed through standardized tests • Results of a standardized test often produce a normal distribution

20. The Normal Distribution

21. The Normal Distribution • Characteristic of most biological and psychological measurements • Mean • midpoint (average) of the distribution • Standard Deviation • a measure of variability around the mean

22. The Case Study • Intensive investigation of a single individual over time • Limited in generalizability • do the results apply to other people?

23. Surveys • Assessing groups of individuals • often used to determine attitudes and abilities • Usually use a sample rather than an entire population

24. Correlational Research • Finding the relationship between two variables • Often described in the scatterplot • a distribution of data points that vary in two dimensions

25. Scatterplot Table 2.1

26. Correlation Coefficient • A measure of the relationship between two variables • Range: +1.0 : perfect positive correlation 0.0 : no correlation -1.0 : perfect negative correlation • Coefficient usually not perfect • e.g. +0.7

27. Positive Correlation

28. No Correlation Math Performance Shoe Size

29. Negative Correlation Reliability Age of Car

30. What do Correlations mean? • Imply that two scores are related • Does not imply causation

31. Biases • Observer Expectancy Effects • Observer Bias • the tendency of an experimenter to make biased observations • Subject Expectancy Effects • Demand Characteristics • the expectations a subject brings that may influence the outcome of an experiment

32. Controls for Biases • Double-Blind Experiment • neither the experimenter nor the subject are aware of the treatment condition • reduces observer bias and subject expectancy • Matched-Groups Design • matching groups of subjects to control for variables that might influence outcome • e.g. subjects in both groups matched for age or sex

33. Epidemiological Research • The use of correlational techniques for establishing relationships between behavior and health • e.g. relationship between smoking and mortality • Limited in determining causal connections • Cannot control confounding variables • e.g. genetic predispositions

34. Inventories and Questionnaires • Tests that correlate with other skills • e.g. SAT, ACT, MCAT, WAIS • Often administered as “Paper and Pencil” tests

35. Reliability • Extent to which repeating a test will generate a similar result • test-retest reliability • alternate-form reliability • split-half reliability

36. Validity • The ability of a test to measure what it was designed to measure • face validity • criterion-related validity

37. Ethical Issues • Institutional Review Boards (IRBs) review research to consider issues like: • Does the research consider the welfare of the subjects? • Is it justifiable? • Is privacy ensured? • Is the subject informed of the outcome? • can the subject give informed consent?