Psychology 611Advanced Statistical and Research Methods for Psychology IFALL 2011Instructor: Patrick E. McKnight, Ph.D.Office: David King 2064/2065Office Hours: Tues 3:00pm-4:00pm and by appointmentPhone: (703) 993-8292E-mail: [email protected] Location: STII 15Class Date/Time: Tues 4:30pm-7:10pmClass website: http://mres.gmu.edu/PSYC611/TA: Simone ErchovTA email: [email protected] Office: David King 2064TA Office Hours: Thur 7-8pmFri 11:30-12:30amCourse OverviewPsychology 611 is the first 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 statis-tical terminology, apply your knowledge in 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 ought to recognize and understand the followingconcepts and terms: measures of central tendency (e.g., mean,median, mode), measures of dispersion (e.g., variance, standarddeviation, range), tests of difference (e.g., t-tests, ANOVA),measures of association (e.g., correlation, covariance), tests ofassociation (e.g., multiple regression, chi-square), and researchdesign. Students who recognize that they are not prepared totake the course will be strongly encouraged to take a moreintroductory course.Required Textbooks2 StatSoft, Inc. (2010). Electronic Statis-tics Textbook. Tulsa, OK: StatSoft. WEB:http://www.statsoft.com/textbook/. - referred to as SS2 Vickers, A.J. (2009). What is a p-value anyway? 34 storiesto help you understand statistics. Addison Wesley. (ISBN:978-0321629302)2 Bruning, J.L. and Kintz, B.L. (1997). Computational hand-book of statistics (4th Edition). Allyn & Bacon. (ISBN:978-0673990853).2 Iversen, G.R. and Norporth, H. Analysis of Variance (SageUniversity Paper Series on Quantitative Applications in theSocial Sciences, No. 07-001). Newbury Park, CA: Sage.(ISBN: 978-0803930018)2 Carmines, E.G. and Zeller, R.A. (1979). Reliability and Va-lidity Assessment. (Sage University Paper Series on Quan-titative Applications in the Social Sciences, No. 07-017).Newbury Park, CA: Sage. (ISBN: 9780803913714)2 Lewis-Beck, M.S. (1976). Applied Regression: An Introduc-tion. (Sage University Paper Series on Quantitative Appli-cations in the Social Sciences, No. 07-022). Newbury Park,CA: Sage. (ISBN: 0-8039-1494-6)2 Fox, J. (1991). Regression diagnostics. (Sage UniversityPaper Series on Quantitative Applications in the Social Sci-ences, No. 07-079). Newbury Park, CA: Sage. (ISBN:00-8039-3971-X)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 both1books to all students since we all struggle with writing and ba-sic concepts. These books present both topics in very easilydigestible 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. These additional and optional readings are requiredreading for students seeking to get an “A” in the course. Pleaseread on for more information.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 than3 weeks following that lecture. Each student may retake oneand only one module after failure. Due