Psychology as a Science

1. Psychology as a Science • In this lecture we will discuss: • science - a method for understanding • limits of common sense • methods of science • description • correlation • experimentation • evaluating data with statistics • sources of error and bias in research

2. Science vs. Common Sense • Common sense and intuition often tell us about psychology • e.g., suppose a study tells us that ‘separation weakens romantic attraction’ • common sense may tell us - “out of sight, out of mind” • or common sense may say the opposite - “absence makes the heart grow fonder” • Common sense can be inconsistent and based on hindsight

3. Science vs. Common Sense • Science helps build explanations that are consistent and predictive rather than conflicting and postdictive (hindsight) • Science is based on • knowledge of facts • developing theories • testing hypotheses • public and repeatable procedures

4. Scientific Inquiry • Facts are what need to be explained • objective - viewable by others • based on direct observation • reasonable observers agree are true • Theory is a set of ideas that • explains facts • makes predictions about new facts • Hypothesis • prediction about new facts • can be verified or falsified

5. Methods in Psychology • Setting - field vs. laboratory • Methods of data collection • self-report vs. observational • Research plan or design • descriptive • correlational • experimental

6. Descriptive Study • Describes a set of facts • Does not look for relationships between facts • Does not predict what may influence the facts • May or may not include numerical data • Example: measure the % of new students from out-of-state each year since 1980

7. Correlational Study • Collects a set of facts organized into two or more categories • measure parents disciplinary style • measure children’s behavior • Examine the relation between categories • Correlation reveals relationships among facts • e.g., more democratic parents have children who behave better

8. Correlational Study • Correlation cannot prove causation • Do democratic parents produce better behaved children? • Do better behaved children encourage parents to be democratic? • May be an unmeasured common factor • e.g., good neighborhoods produce democratic adults and well behaved children

9. Experiments • Direct way to test a hypothesis about a cause-effect relationship between factors • Factors are called variables • One variable is controlled by the experimenter • e.g., democratic vs. authoritarian classroom • The other is observed and measured • e.g., cooperative behavior among students

10. Experimental Variables • Independent variable • the controlled factor in an experiment • hypothesized to cause an effect on another variable • Dependent variable • the measured facts • hypothesized to be affected

11. Independent Variable • Must have at least two levels • categories - male vs. female • numeric - ages 10, 12, 14 • Simplest is experimental vs. control • experimental gets treatment • control does not

12. Experimental Design • Levels may differ between or within people • Within-subject experiment - different levels of the independent variable are applied to the same subject • Between-groups experiment - different levels of the independent variable are applied to different groups of subjects

13. Experimental Design • Random sample - every member of the population being studied should have an equal chance of being selected for the study • Random assignment - every subject in the study should have an equal chance of being placed in either the experimental or control group • Randomization helps avoid false results

14. Research Settings • Laboratory • a setting designed for research • provide uniform conditions for all subjects • permits elimination of irrelevant factors • may seem artificial • Field research • behavior observed in real-world setting • poor control over conditions • measures may be more representative of reality

15. Data-Collection Methods • Self-report - procedures in which people rate or describe their own behavior or mental state • questionnaires • rating scales • on a scale from 1 to 7 rate your opinion of … • judgements about perceptions • on a scale from 1 to 100 how hot is ...

16. Data-Collection Methods • Observational methods - researchers directly observe and record behavior rather than relying on subject descriptions • naturalistic observation - researcher records behavior as it occurs naturally • tests - researcher presents stimuli or problems and records responses

17. Descriptive Statistics • Variable - something that can vary or change • Dependent variable - something we measure • Data - a collection of measurements • Statistics - summary descriptions of data (i.e., mean, medium, range)

18. Descriptive Statistics • Used to describe or summarize sets of data to make them more understandable • measures of central tendency • mean, median, mode • measures of variability • range, standard deviation • measures of association • correlation coefficient

19. Measures of Central Tendency • What is the average family income above? • Mean - the arithmetic average • Median - the center score • Mode - the score that occurs the most

20. Measures of Variability • Range - the difference between the highest and lowest score in a set of data • Standard deviation - reflects the average distance between every score and the mean

21. Correlation Coefficient • Often we measure more than one variable • Grade point and SAT score • Are they related? • Correlation statistic is a way to find out

22. Correlation Coefficient • Measures whether two variables change in a related way • Can be positive (max +1.00) • Negative (min -1.00) • Or not related! (~ 0.0)

23. Inferential Statistics • Descriptive statistics summarize a data set • We often want to go beyond the data • Is the world at large like my sample? • Are my descriptive statistics misleading? • Inferential statistics give probability that the sample is like the world at large

24. Statistics and Probability • Probability means how likely something is • How likely are results like mine to occur by chance? • Statistical inferences • significant result - reflects the real world rather than chance, with high probability (e.g., > .95 ) • not significant - results reflect chance

25. Measurement Errors • Why is inference based on probability instead of certainty? • Data can be misleading because of variability • low variability • high variability

26. Measurement Errors • Why is inference based on probability instead of certainty? • Data can be misleading because of bias • low bias • high bias

27. Variability Bias Variability & Bias Measurement Error • Variability and bias can combine

28. Sources of Bias • Biased sample - when the members of a sample differ in a systematic way from the larger population the researcher is interested in • Example • interested in all voters • contact by telephone • biased sample - lower economic groups may not own telephones

29. Sources of Bias • Observer-expectancy effect • researcher has expectations that influence measurements • Subject-expectancy effect • subject knows design and tries to produce expected result • Blinding • minimize expectancy by removing knowledge about experimental conditions

30. Blinding • Single-blind study - when subjects are kept uninformed as to the treatment they are receiving • Double-blind study - when both subjects and experimenter are kept uninformed about aspects of the study that could lead to differential expectations

31. Ethical Issues in Psychological Research • Right to privacy • Informed consent • use of deception • Animal rights • Is there justification for discomfort or harm a research procedure may produce? • APA publishes ethical guidelines