Experimental and Quasi-experimental Method

1. Experimental and Quasi-experimental Method September 16,2008

2. Learning Objectives • Review APA reference list • Gain some experience with experimental/quasi-experimental designs. • Learn how to use excel to analyze experimental data. • Continue with introduction to writing a scientific paper.

3. References References Brown, W. M., & Moore, C. (2002) Fluctuating asymmetry and romantic jealousy. Evolution and Human Behavior, 24, 113-117. Buss, D. M. & Greiling, H. (1999). Adaptive individual differences. Journal of Personality, 67(2),209-243. Buss, D. M. (1991). Evolutionary personality psychology. Annual Review of Psychology, 42, 459-491. Buss, D. M. (1997). Evolutionary foundations of personality. In Hogan, R., (Ed.), Handbook of personality psychology (pp. 317-344). London: Academic Press. Buss, D. M. (2000).  The dangerous passion: Why jealousy is as necessary as love and sex. New York: Free Press.  

4. First Data Collection • This time you will be the participants. • We are going to run a quasi-experiment • For now you do not need to know what are the conditions of the quasi-experiment.

5. Instructions • Go to http://www.thewritingpot.com/stroop/

6. Instructions • Go to http://www.thewritingpot.com/stroop/ • There are going to be a series of colored words.

7. Instructions • Go to http://www.thewritingpot.com/stroop/ • There are going to be a series of colored words. • Your task is to hit the key which corresponds to the color of the word not what it says.

8. Instructions • Go to http://www.thewritingpot.com/stroop/ • There are going to be a series of colored words. • Your task is to hit the key which corresponds to the color of the word not what it says. • If you are ready go ahead and click on try experiment and then hit space bar.

9. Stroop Effect Continued • When you are done write down click on view results. • Write down the average time for words which were different for the color and the amount of time it took for words which matched the color. • Now repeat this entire process two more times.

10. Microsoft Excel • Open a new database. • Write the following variable names: congruent1, congruent2, congruent3,averagecongruent, noncongruent1, noncongruent2, noncongruent3, average congruent. • Enter your scores from the experiment.

11. Calculating a mean in Excel • In the cell under average congruent type =average( • Type a2:c2) or highlight the cells which contain your congruent data. • In both cases you should have something like the following : =average(a2:c2) • Do the same for non congruent variables

12. Were you strooped?

13. Were you strooped? • First you might want to plot mean stroop effects. • To do this highlight the Average stroop scores for congruent and non-congruent • In this case the ctrl button is helpful. • First highlight one press control and highlight the other. • Now click on insert graph • Pick the bar graph • Hit enter • If your non-congruent stroop average score was higher than the average congruent score you were strooped

14. Here are my scores

15. Did your performance improve? • How would we know? • We could plot the learning curve for each condition. • First highlight your congruent1, congruent2, and congruent3 scores. • Now make a similar graph as before.

16. My Improvement

17. Was the Class Strooped? • First we have to enter data. • We already have the variable names in our database. • I’m going to call each of you one at a time. • I want everyone to enter their classmate’s scores. • I also want them to record each participant’s sex

18. The Dataset

19. Let’s Do a T-Test • On toolbar on top click “Tools” dropdown box will appear – Choose “Data Analysis” then . . . • Click “t-test: 2 samples assuming equal variance.” • Highlight data: You should see a box with room to enter numbers for “Variable 1 range” and “Variable 2 range.” • Hit Enter

20. Are males more easily strooped?:Our quasi-experiment • concept is the same • comparing means • analysis is a bit more complicated • What do we need to do?

21. Are males more easily strooped? • concept is the same • comparing means • analysis is a bit more complicated • What do we need to do? • Hint- What are our independent variables

22. Data Manipulation • How do we calculate this difference score? • First type “=(“ in cell J2 • This creates a new variable. • If you want you could name it stroop score. • Highlight the noncongruent average • (cell H2 if you followed my example) • Follow that with a – sign • Then Highlight the congruent average • (cell d2) • The final product should read =(H2-D2)

23. Data Manipulation • Now highlight cell J2 • There will be a little box on the border of that cell • Click and drag it down to the end of the data set. • This will give you the stroop score for each person. • Positive numbers mean they were strooped negative or scores of zero means they were not.

24. Now the Dependant Variable • We have to sort the data set • We need all the males in one section and all the female data on the other. • Highlight all the data by clicking on the top left hand corner of the spreadsheet. • Click on data • Click on sort • Sort by the column for the variable sex.

25. Let’s Do a T-Test • On toolbar on top click “Tools” dropdown box will appear – Choose “Data Analysis” then . . . • Click “t-test: 2 samples assuming equal variance.” • Highlight data: You should see a box with room to enter numbers for “Variable 1 range” and “Variable 2 range.” • This type highlight the difference scores for one of the sexes for “variable 1 range” and highlight the difference scores for the other sex “variable 2 range” • Hit Enter

26. Assignment • I want you to write up a methods and results section for the quasi-experiment we just conducted. • See pages 367 and 368 in the Leary book.