Psychology 612Advanced Statistical and Research Methods for Psychology IISPRING 2009Instructor: Patrick E. McKnight, Ph.D.Office: David King 2064/2065Office Hours: Wed 11:10am-1:10pm and by appointmentPhone: (703) 993-8292E-mail: [email protected] Location: IN 132Class Date/Time: Tues & Thurs 9:00am-10:15amClass website: http://mres.gmu.edu/PSYC612/TA: Kate LaPortTA email: [email protected] Office: Robinson B215CLab Sections: 201, 202 & 207TA Office Hours: Tues 10:15am-11:45amCourse OverviewPsychology 612 is the second course of a two-course sequencethat serves to introduce psychology graduate students to statis-tics, research methodology, research design, and measurement.Traditional graduate psychology statistics courses emphasizestatistical techniques as a matter of declarative knowledge. Stu-dents are expected to know each procedure and its “appropri-ate” application. An alternative approach tends toward techni-cal discourse (e.g., matrix algebra, formula memorization, andhand calculations) and requires greater attention to minute de-tail and mathematical vernacular. A less used but equally suit-able approach treats statistics as a method of principled ar-gument. The method I use for this course is a hybrid of thethree approaches. You will be expected to know the statisti-cal terminology, apply your knowledge in a both carrying outthe procedures as well as interpreting the results, and then youwill be expected to use the results in a manner consistent withscientific discourse.Course ObjectivesThe purpose of this course is to further your introduction todata analysis, research design, and measurement. Your coursework to date ought to have prepared you well by covering mea-sures of central tendency, measures of dispersion, measuresof association, and measures of difference. Due to time con-straints, I do not intend to review these terms or their purposesso I urge every student to review that material prior to thiscourse. What I do intend to cover is a comprehensive view ofunivariate, bivariate and multivariate statistics - why we usestatistics, why you should learn these tools, and what are themost important features to learn and understand. You will gainpractical skills in interpreting, applying and explaining statisti-cal procedures. The combination of an interactive lecture anda weekly laboratory will offer each student the opportunity tosee the procedures, conduct the procedures yourselves, and thenteach one another what you learned. This approach is the com-mon medical model of education - see one, do one, and teachone - that results in better retention and deeper understanding.Course Pre-requisitesStudents are required to earn a “B” or better in PSYC 611(or equivalent) to enroll in PSYC 612. Additionally, studentsought to understand the following concepts and terms: mea-sures of central tendency (e.g., mean, median, mode), measuresof dispersion (e.g., variance, standard deviation, range), testsof difference (e.g., t-tests, ANOVA), measures of association(e.g., correlation, covariance), tests of association (e.g., multi-ple regression, chi-square), and research design. Students whorecognize that they are not prepared to take the course will bestrongly encouraged to take a more introductory course.Required Textbooks2 Field, A. (2005). Discovering Statistics Using SPSS. New-bury Park, CA: Sage. (ISBN: 978-0761944522)2 Dunteman, G.H. and Lewis-Beck, M.S. (1989). Princi-pal component analysis. (Sage University Paper Series onQuantitative Applications in the Social Sciences, No. 07-069). Newbury Park, CA: Sage. (ISBN: 9780803931046)2 Kim, J. and Mueller, C.W. (1978). Introduction to factoranalysis: What it is and how to do it. (Sage UniversityPaper Series on Quantitative Applications in the Social Sci-ences, No. 07-013). Newbury Park, CA: Sage. (ISBN:0-8039-1165-3)2 Iacobucci, D. (2008). Mediation Analysis. (Sage Univer-sity Paper Series on Quantitative Applications in the SocialSciences, No. 07-156). Newbury Park, CA: Sage. (ISBN:9781412925693)2 Klockars, A.J. and Sax, G. (1986). Multiple comparisons.(Sage University Paper Series on Quantitative Applicationsin the Social Sciences, No. 07-061). Newbury Park, CA:Sage. (ISBN: 9780803920514)2 Pampel, F.C. (2000). Logistic regression: A primer. (SageUniversity Paper Series on Quantitative Applications in theSocial Sciences, No. 07-132). Newbury Park, CA: Sage.(ISBN: 9780761920106)Optional TextbooksStudents who struggle with general writing or basic under-standing of statistical terminology may benefit from Zinsser’sbook “On writing well” and Gonick and Smith’s humorous “Thecartoon guide to statistics”, respectively. I recommend bothbooks to all students since we all struggle with writing and ba-sic concepts. These books present both topics in very easily1digestible formats.2 Zinsser, W. (2006). On writing well, 30th Anniversary Edi-tion: The classic guide to writing nonfiction. Colllins: NewYork.2 Gonick, L and Smith, W. (1994). The cartoon guide tostatistics. HarperCollins: New York.Students who are interested in more than just the general“nuts and bolts” of the standard statistical procedures oughtto consult the following books. Many of the points I make inclass come from these books but it is always best to read themfrom a more original source.2 Abelson, R.P. (1995). Statistics as principled argument.Lawrence Erlbaum Associates, Hillsdale, NJ. (ISBN: 0-8058-0528-1).2 van Belle, G. (2002). Statistical rules of thumb. Wiley-Interscience: New York. (ISBN: 0-4714-0227-3)Additional ReadingAt times I will post additional readings that are optional(and free) for all students. Many of these readings provide ex-cellent examples of the topics we discuss in class. Please seethe course website for links to the electronic versions of thesereadings.Grading CriteriaGrades will be determined by each student’s observed per-formance on four statistics modules. Each student must per-form the statistical procedures in the presence of the TA orthe instructor and demonstrate proficiency. There will be a15 minute time limit on the performance; speed and fluency ofyour performance will be indicative of your proficiency. Stu-dents may complete a module (i.e., demonstrate proficiency)at any time after the last module lecture but no later than 3weeks following that lecture. Each student may retake one andonly one module after failure. Due to limited resources, wemust limit the number of retakes to one and the retake mustbe