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Courses

Spring Quarter 2013
CS&SS 221: Statistical Concepts and Methods for the Social Sciences (5); Day: MTWThF; Time: 9:30-10:20am (MWF); Room: JHN 1025(MWF); 8:30-9:20pm (TTh) (QZ AA), LOW 201; 9:30-10:20pm (TTh) (QZ AB), DEM 112; 8:30-9:20pm (TTh) (QZ AC), LOW 105; 9:30-10:20pm (TTH) (QZ AD), LOW 201; 8:30-9:20pm (TTh) (QZ AE), DEN 112; 9:30-10:20pm (TTH) (QZ AF), LOW 205; Instructor: Nathalie Williams; Develops statistical literacy. Examines objectives and pitfalls of statistical studies; study designs, data analysis, inference; graphical and numerical summaries of numerical and categorical data; correlation and regression; and estimation, confidence intervals, and significance tests. Emphasizes social science examples and cases. (Students may receive credit for only one of STAT 220, STAT 311, STAT/CS&SS/SOC 221, and ECON 311.); Offered jointly with SOC 221/STAT 221; AWSp.
CS&SS 503: Advanced Quantitative Political Methodology (5); Day: ThF; Time: 1:30-4:20pm (Th)
1:30-3:20pm (F); Room: SMI 220(ThF); Instructor: Matt Barreto; Prerequisites: POL S 500, POL S 501.; Theory and practice of likelihood inference. Topics covered include probability modeling, maximum likelihood estimation, models for binary responses, count models, sample selection, and basis time series analysis.; Offered jointly with POL S 503.
CS&SS 505: Review of Mathematics for Social Scientists (1); Day: T; Time: 12:30-1:20pm; Room: THO 325; Instructor: Adrian E. Raftery; Reviews basic mathematical skills needed for a meaningful understanding of elementary statistics, data analysis, and social science methodology. Overview of core knowledge required for graduate courses in quantitative methods in social sciences. Topics include discrete mathematics, differential and integral calculus, review of matrix algebra, and basic probabilistic and statistical concepts.
CS&SS 507: Methodology: Quantitative Techniques in Sociology (3) I&S; Day: TTh; Time: 1:30-3:20pm (TTh); Room: LOW 113; Instructor: Tyler H. McCormick; Applied regression analysis with emphasis on interactive computer graphics techniques and interpretation. Application to typical sociological problems.; Offered jointly with SOC 506.
CS&SS 527: Survey Research Methods (3); Day: MW; Time: 10:30-11:50am; Room: HSR RR134; Instructor: Ali Mokdad; Prerequisites: HSERV 511, HSERV 512, HSERV513; BIOST 517, BIOST 518; or EPI 512, EPI 513; Provides students with skills in questionnaire development and survey methods. Develops a questionnaire and designs a survey research proposal on a health-related or social topic.; Offered: jointly with HSERV 527.
CS&SS 529: Sample Survey Techniques (3); Day: TTh; Time: 10:30-11:50pm; Room: LOW 105; Instructor: Elena Erosheva; Prerequisites: STAT 421, STAT 423, STAT 504, QMETH 500, BIOST 511, or BIOST 517, or equivalent; Recommended: CS&SS 505-506 or equivalent.; Design and implementation of selection and estimation procedures. Emphasis on human populations. Simple, stratified, and cluster sampling; multistage and two-phase procedures; optimal allocation of resources; estimation theory; replicated designs; variance estimation; national samples and census materials.; Offered: jointly with BIOST 529/STAT 529.
CS&SS 560: Hierarchical Modeling for the Social Sciences (4); Day: MWThF; Time: 2:30-3:20pm (MWThF); Room: MGH 287 (MWF)
MGH 228 (Th); Instructor: Adrian Dobra; Prerequisites: SOC 504, SOC 505, SOC 506 or equivalent; Recommended: CS&SS 505, CS&SS 506 or equivalent; Explores ways in which data are hierarchically organized, such as voters nested within electoral districts that are in turn nested within states. Provides a basic theoretical understanding and practical knowledge of models for clustered data and a set of tools to help make accurate inferences.; Offered jointly with STAT 560/SOC 560.
CS&SS 564: Bayesian Statistics for the Social Sciences (4); Day: TTh; Time: 10:30-11:50am (TTh)
1:30-2:20pm (Th); Room: GLD 435 (TTh)
CDH 110B(Th); Instructor: Adrian Dobra; Prerequisites: SOC 504-505-506 or equivalent.; Recommended: CS&SS 505-506 or equivalent.; Statistical methods based on the idea of probability as a measure of uncertainty. Topics covered include subjective notion of probability, Bayes' Theorem, prior and posterior distributions, and data analysis techniques for statistical models.; Offered jointly with STAT 564.
CS&SS 590: CSSS Seminar (1); Day: W; Time: 12:30-1:20pm; Room: SAV 164; Instructor: Brian Flaherty; This course offers a stimulating intellectual interaction among faculty and students by running a dynamic seminar series featuring presentations of ongoing social science research that involves cutting edge statistical methods.
CS&SS 594: Special Topics in Social Science and Statistics: Multiway Data Analysis(4); Day: TTh; Time: 11:30-12:50pm; Room: PDL C301; Instructor: Peter Hoff

Courses

Spring Quarter 2013