SR 111. Research Methods and Statistics Fall, 1997 Dr. John B. Gatewood (Instructor) John R. Palaia (A.T.) 10C Price Hall 16 Price Hall 758-3814 / JBG1 758-3810 / JRP3 Overview This course is an introduction to social science research methods and to elementary statistics. Methods are explicit ways of gathering information. Statistics are numerical procedures for manipulating, describing, and making inferences from existing information. Thus, methods and statistics are very interrelated subjects (which is why we teach both subjects in the same four-hour course). Used in concert, explicit methods and subsequent statistical analyses distinguish social science propositions from mere opinions. Whereas all of us have opinions, science requires that propositions be evaluated with respect to publicly available evidence (data). Further, scientific propositions must be testable (capable of being shown false) with respect to explicitly defined and replicable data: "This is what I did, this is what I found, this is my interpretation of the findings. I'm not asking you just to believe me -- you can collect your own data and draw your own conclusions." The point is that simply asserting such-and-such is true will not convince skeptics. They require supporting evidence and argumentation, and science is a particular way of arguing knowledge claims. For the first third of the semester, we will focus on social science research methods, concluding the section with an hour exam. I've chosen to cover these topics first because methods for obtaining data temporally precede data analysis in the daily business of social research. However, we will devote only a third of the semester to these important matters because (a) Babbie's book is exceedingly clear and thorough, and (b) methods are less technical ("easier" to understand) than statistics for most social science majors. With the rapid overview of research methods behind us, we will proceed somewhat more leisurely through Runyon and Haber's elementary statistics text. Some topics occupy only a single class period, but others -- ones I feel are especially important and/or difficult -- are scheduled over several days. All of the statistics covered in this course require only high school mathematics (i.e., arithmetic and algebra), but do not fall behind. Like any mathematics (or foreign language) course, statistics involve cumulative knowledge. So, if you should have trouble understanding something, come see me and/or the teaching assistant without delay. We're available, ready, and willing to help. If you work hard and I don't get diverted, we may actually get through all the statistics I've scheduled! (If not, then I'll have to adjust the schedule and assignments as the semester progresses.) One final thought. Some of you are taking this course because you want to do social research yourself, whether writing a senior thesis, going on to graduate school, or working in careers like marketing, personnel, social services, etc. That goal is consistent with the course objectives, and I hope the course will meet your needs. Others of you are taking the course simply because it is required in your major, i.e., you have no desire to conduct social research yourself. That's okay, too. Your goal for the course should be learning enough about methods and statistics to understand published social science literature, as well as news stories. As H.G. Wells said about century ago, "Statistical thinking will one day be as necessary for efficient citizenship as the ability to read and write." That day is nigh upon us. Materials There are three required books for the course, two dealing with research methods and one on elementary statistics. These are available in the bookstore and should be purchased, underlined, and kept for future reference. Babbie, Earl (1995) Research Methods for Social Science, 7th Edition. Belmont, CA: Wadsworth Publishing. Weller, Susan C. and A. Kimball Romney (1988) Systematic Data Collection. Newbury Park, CA: Sage Publications. Runyon, Richard P., Audrey Haber, David J. Pittenger, and Kay A. Coleman (1996) Fundamentals of Behavioral Statistics, 8th Edition. New York: McGraw-Hill. Requirements The formal requirements for the course are three hour exams, homework assignments, a term paper, and class participation. The relative weighting of these is as follows: First exam (methods) 100 pts. Second exam (descriptive statistics) 100 pts. Third exam (inferential statistics) 150 pts. Homework * 100 pts. Research proposal * 100 pts. Class participation 50 pts. (* Assignments/Instructions will be distributed separately.) Your course grade will be determined by how many points you earn divided by the total possible. A score of 90% or higher is an A, 80% to 89% is an B, ... below 60% is an F. In short, I do not grade on a "curve" -- I do not pre-determine the percentages of A, B, C, D, and F's to be given. Everyone can earn an A or everyone fail; you are not in direct competition with each other. Finally, and before anyone has sinned, please pay special attention to the following "ground rules" for this course: Rule #1. Helping one another understand general concepts and procedures is encouraged. But, helping one another with the specifics of a take-home assignment constitutes academic dishonesty and will be punished accordingly. Rule #2. Attendance is required. Rule #3. Failure to take an exam as scheduled will result in a "zero" for that assignment. Rule #4. The penalty for failing to turn in homework assignments or the term paper when they are due is 10% of the assignment's total point-value for each 24-hour period (or portion thereof) that the assignment is late, weekends and holidays included. Rule #5. Any student having a legitimate reason for missing an exam or turning in work late must obtain MY approval (John Gatewood's) in advance, i.e., simply failing to show up, calling the Department office and leaving a message, or talking with the Teaching Assistant is not sufficient. Class Periods by Calendar Days Monday Tuesday Wednesday Thursday Friday * --- --- Aug 27 --- Aug 29 Sept 1 --- Sept 3 --- Sept 5 Sept 8 --- Sept 10 --- Sept 12 Sept 15 --- Sept 17 --- Sept 19 Sept 22 --- Sept 24 --- Sept 26 Sept 29 --- Oct 1 --- --- Oct 6 --- Oct 8 ("Fri") --- Oct 10 Oct 13 --- Oct 15 --- Oct 17 Oct 20 --- Oct 22 --- Oct 24 Oct 27 --- Oct 29 --- Oct 31 Nov 3 --- Nov 5 --- Nov 7 Nov 10 --- Nov 12 --- Nov 14 Nov 17 --- Nov 19 --- Nov 21 Nov 24 --- Nov 26 --- --- Dec 1 --- Dec 3 --- Dec 5 * Remember that all our "Friday" classes meet for 2 hours. Schedule of Topics and Assignments RESEARCH METHODS . . . 1. Aug 27 (W) General Introduction "Science" as a Way of Knowing Readings: Babbie, Overview & Chpt. 1 (pp. 1-38) 2. Aug 29 (F) Theory and Research Readings: Babbie, Chpt. 2 (pp. 39-62) 3. Sept 1 (M) The Nature of Causation Readings: Babbie, Chpt. 3 (pp. 63-79) 4. Sept 3 (W) Research Design Readings: Babbie, Chpt. 4 (pp. 80-108) 5. Sept 5 (F) Conceptualization and Measurement Readings: Babbie, Chpt. 5 (pp. 109-130) 6. Sept 8 (M) Operationalization Readings: Babbie, Chpt. 6 (pp. 131-159) 7. Sept 10 (W) Indexes, Scales, and Typologies Readings: Babbie, Chpt. 7 (pp. 160-185) 8. Sept 12 (F) The Logic of Sampling Readings: Babbie, Chpt. 8 (pp. 186-229) 9. Sept 15 (M) Experiments Readings: Babbie, Chpt. 9 (pp. 232-254) 10. Sept 17 (W) Survey Research Readings: Babbie, Chpt. 10 (pp. 255-278) 11. Sept 19 (F) Field Research Readings: Babbie, Chpt. 11 (pp. 279-304) 12. Sept 22 (M) Unobtrusive Research Readings: Babbie, Chpt. 12 (pp. 305-336) 13. Sept 24 (W) Evaluation Research Readings: Babbie, Chpt. 13 (pp. 337-359) 14. Sept 26 (F) ----- FIRST HOUR EXAM ----- STATISTICS . . . 15. Sept 29 (M) Statistical Analysis and Basic Mathematical Concepts Readings: Runyon, Haber, et al., Chpts. 1 & 2 (pp. 1-62) 16. Oct 1 (W) Frequency Distributions and Percentiles Readings: Runyon, Haber, et al., Chpt. 3 (pp. 67-98) 17. Oct 6 (M) Graphs and Tables Readings: Runyon, Haber, et al., Chapt. 6 (pp. 185-212) 18. Oct 8 (W/"F") Measures of Central Tendency Readings: Runyon, Haber, et al., Chpt. 4 (pp. 107-136) 19. Oct 10 (F) Measures of Dispersion Standard Normal Distribution Readings: Runyon, Haber, et al., Chpt. 5 (pp. 143-179) 20. Oct 13 (M) Correlation Readings: Runyon, Haber, et al., Chpt. 7 (pp. 219-255) 21. Oct 15 (W) Correlation Readings: Runyon, Haber, et al., Chpt. 7 (pp. 219-255) 22. Oct 17 (F) Regression and Prediction Readings: Runyon, Haber, et al., Chpt. 8 (pp. 265-301) 23. Oct 20 (M) REVIEW -- Descriptive Statistics for Interval Variables Readings: Runyon, Haber, et al., re-read Chpts. 4, 5, 7, 8 24. Oct 22 (W) ----- SECOND HOUR EXAM ----- 25. Oct 24 (F) Probability Readings: Runyon, Haber, et al., Chpt. 9 (pp. 307-348) 26. Oct 27 (M) Introduction to Statistical Inference Readings: Runyon, Haber, et al., Chpt. 10 (pp. 355-391) 27. Oct 29 (W) Statistical Inference: Single Samples Readings: Runyon, Haber, et al., Chpt. 11 (pp. 395-433) 28. Oct 31 (F) REVIEW -- Statistical Inference for Single Samples Readings: Runyon, Haber, et al., review Chpts. 10-11 29. Nov 3 (M) Statistical Inference: Two-Sample Case Readings: Runyon, Haber, et al., Chpt. 12 (pp. 437-476) 30. Nov 5 (W) Statistical Inference: Two-Sample Case (continued) Readings: Runyon, Haber, et al., Chpt. 12 (pp. 437-476) 31. Nov 7 (F) REVIEW -- Student's t-test Readings: Runyon, Haber, et al., re-read Chpt. 12 32. Nov 10 (M) Introduction to Analysis of Variance Readings: Runyon, Haber, et al., Chpt. 13 (pp. 483-528) 33. Nov 12 (W) Introduction to Analysis of Variance (continued) Readings: Runyon, Haber, et al., Chpt. 13 (pp. 483-528) 34. Nov 14 (F) REVIEW -- Oneway ANOVA Readings: Runyon, Haber, et al., re-read Chpt. 13 35. Nov 17 (M) Statistical Inference: Categorical Variables Readings: Runyon, Haber, et al., Chpt. 15 (pp. 575-601) 36. Nov 19 (W) Statistical Inference: Categorical Variables Readings: Runyon, Haber, et al., Chpt. 15 (pp. 575-601) 37. Nov 21 (F) ----- THIRD HOUR EXAM ----- 38. Nov 24 (M) Statistical Inference: Ordinally Scaled Variables Readings: Runyon, Haber, et al., Chpt. 16 (pp. 605-616) 39. Nov 26 (W) Statistical Inference: Ordinally Scaled Variables Readings: Runyon, Haber, et al., Chpt. 16 (pp. 605-616) THE "BIG PICTURE" . . . 40. Dec 1 (M) The Ethics and Politics of Social Research Readings: Babbie, Chpt. 18 (pp. 445-466) 41. Dec 3 (W) The Uses of Social Research Readings: Babbie, Chpt. 19 (pp. 467-476) 42. Dec 5 (F) Course Summary & Student Evaluations