PSY 301 Lab

1. PSY 301 Lab Week 4 Correlational Research

2. Agenda • Turn in Method/Results paper • Correlational Research • Survey Time • Entering data • No Homework

3. What are correlations? • In correlational research, we look to see if one variable changes with another (covaries). • We can also call this an association. • We use correlational research when we cannot assign experimental groups due to ethics or practicality • Ex) Smoking, disease, gender

4. Correlations • Assess the relationships among naturally occurring variables with the goal of identifying predictive relationships. • Correlations have both strength and direction

5. Correlation Is NOT Causation THE MOST IMPORTANT RULE IN CORRELATIONAL RESEARCH!!!

6. Why Correlation Causation Does Not Equal Causation • Correlation: means 2 variables are related • We can make predictions based on correlations • We CANNOT infer cause of the relationship • “Spurious” relationship: when the relation between 2 variables can be explained by a 3rd.

8. It has been found that cities with a high number of churches per capita also have a high number of adult bookstores per capita. Explain why this is an example of why correlation is not causation. Correlation, Causation (cont’d)

9. What statistics do we use with correlations? • There are many statistics available for measuring the strength of correlations. • For this class we will be using the Pearson product moment correlation • Lower-case r represents Pearson Correlation. • We can even determine inter-rater reliability using Pearson correlations, how?

11. Negative Correlation

12. Positive Correlation

13. More about r • r can range from -1 to +1. • -1 means a perfect negative (inverse) correlation (as X _______, Y _______) • 0 means there is no correlation ( ____ relationship between X and Y) • +1 means a perfect positive correlation (as X _______, Y _______)

14. Other pictures of Scatter Plots

15. Self-Test • A researcher looks at the relationship between how many cookies I eat in a week and the overall degree of satisfaction I have with my life. The researcher tells me she found r = +1.34. What does this tell us?

16. Survey research is correlational • For Surveys we must: • Select a representative sample of the population of interest • Use predetermined set of questions • Scope can be limited and specific, or broad and global • Any examples or ideas for a survey?

17. Sampling • Careful selection allows one to generalize to a population. • Remember, our interest is the population • We want to generalize our results • Biased sample: systematically differs from the characteristics of the population • Selection bias: occurs when procedures used to select a sample result in over/under representation of some segment(s) of the population.

18. Approaches to Sampling • Nonprobability: does not guarantee that every element in the population has an equal chance of being included in the sample • Convenience sampling -- availability and willingness of sample to respond • Ex) Call-in surveys for TV shows • Probability sampling: allows researcher to estimate the likelihood that their findings for the sample differ from those for the population • Ex)Simple random or stratified random sampling

19. General Survey Methods • MAIL • Personal Interviews • Telephone Interviews • Internet Surveys • Pro’s and Con’s of each?

20. Survey-Research Designs • Cross-sectional: one or more samples drawn AT ONE TIME from the population. • Successive independent samples: same questions asked of different respondents over a TIME PERIOD. • Potential problems? • Longitudinal: same respondents surveyed over time in order to look at individuals’ changes • Hard to identify cause of change • Potential threat due to Time?

21. Survey Questions • Demographics: describe characteristics of the people who are surveyed (race, ethnicity, SES, etc.) • Self-report scales: • Can assess attitudes/preferences • -1 = Dislike, 0 = No Opinion, 1 = Like • Do you enjoy Starbucks? • Jazzman’s? • Caribou? • Accuracy of questionnaires depend on careful/expert construction

22. Reliability • Consistency of the items in the measurement across samples • If you administer a scale 3 times, do you get the same/similar item responses each time? • Increased by: 1) using items testing same underlying construct 2) testing across many samples 3) using uniform testing procedures • Test-retest reliability method: give same questionnaire 2X to large sample. • High reliability: Similar result distributions for both administrations • Parrallel form test • 0.8 reliability needed between tests

23. Validity • Validity: truthfulness of the measure • Construct validity: extent to which it measures the theoretical construct it’s designed to measure • Criterion validity: predictive v. concurrent • Convergent validity: the extent to which 2 similar measures correlate with each other in the measure of a theoretical construct (p. 174-175, Shaughnessy). • Discriminant validity: extent to which 2 measures do not correlate with each other in the measurement of a theoretical construct.

24. Please complete the surveys being handed out.

25. The two surveys • Life Satisfaction Survey • Answer the questions honestly • Once you finish, add up your total score from the 5 questions • Perceived Stress Survey • Answer the 10 questions honestly • Once you finish, add up your total score

26. Entering Data into Excel • Enter scores of each question • For both surveys (see excel template) • Enter the Total Score (PSQ Total or SWL Total) for each survey as well • When entering your data, make sure to differentiate the two surveys from each other

27. For Next Class • EMAIL ME (jfedota@gmu.edu) YOUR DATA TODAY • Title the document “lastname.xls” • My Homework: • I will compute correlation • I will put the results on the course webpage • http://archlab.gmu.edu/people/jfedota/teaching.html • YOU Bring these posted results to class next week, and we will interpret them • We’ll talk about writing up the results next week, too