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Registration and Auditing of CSSS Courses for UW Students, UW Employees (Faculty, Staff, other) and Non-UW Individuals

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CSSS Course List 2014-15

UW Course Descriptions and Time Schedule

CSSS Course Catalog

Winter Quarter 2015

CS&SS 221
Statistical Concepts and Methods for the Social Sciences (5) NW, QSR
Time: 9:30-10:20am (MWF)
Room: CDH 109
         8:30-9:20am (TTh) (QZ BA) THO 211
         9:30-10:20am (TTh) (QZ BB) THO 134
         8:30-9:20am (TTH) (QZ BC) THO 235
         9:30-10:20am (TTh) (QZ BD) THO 135
         8:30-9:20am (TTh) (QZ BE) THO 325
         9:30-10:20am (TTh) (QZ BF) THO 211
Instructor: Jeff Arnold
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 221, STAT 311, STAT 221/CS&SS 221/SOC 221, and ECON 311.)
Offered: jointly with SOC 221/STAT 221.

CS&SS 501
Advanced Political Research Design and Analysis (5)
Day: MF
Time: 1:30-4:20pm
Room: SMI 220
          1:30-4:20pm (M) SMI 220
          1:30-3:20pm (F) SMI 220
          1:30-3:20am (F) SAV 167
Instructor: John Wilkerson
Testing theories with empirical evidence. Examines current topics in research methods and statistical analysis in political science. Content varies according to recent developments in the field and with interests of instructor.
Offered: jointly with POL S 501.

CS&SS 504
Applied Regression (4)
Day: MWThF
Time: 2:30-3:20
Room: THO 125
         2:30-3:20pm (MWF) THO 125
         3:30-4:20pm (Th) THO 134
Instructor: Elena Erosheva
Least squares estimation. Hypothesis testing. Interpretation of regression coefficients. Categorical independent variables. Interactions. Assumption violations: outliers, residuals, robust regression; nonlinearity, transformations, ACE, CART; nonconstant variance. Variable selection and model averaging. Prerequisite: either STAT 342, STAT 390/MATH 390, STAT 421, STAT 481/ECON 481, STAT 509/CS&SS 509/ECON 580, or SOC 425; recommended: MATH 308.
Offered: jointly with STAT 504.

CS&SS 505
Review of Mathematics for Social Scientists (1)
Day: Th
Time: 12:30-1:20pm
Room: THO 325
Instructor: Adrian 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. Credit/no-credit only.
Offered: jointly with SOC 512; Sp.

CS&SS 544
Event History Analysis for the Social Sciences (5)
Day: TTh
Time: 10:30-12:20pm
Room: SAV 138
Instructor: Darryl Holman
Examines life course research using event-history analysis with applications to the substantive areas of household dynamics, family formation and dissolution, marriage, cohabitation, and divorce, migration histories, residential mobility, and housing careers. Examines continuous- and discrete-time longitudinal models during practical laboratory sessions.

CS&SS 566
Causal Modeling (4)
Day: MWF
Time: 10:30-11:30am
Room: SMI 115
         10:30-11:30 MWF SMI 115
         11:30-12:20 W SAV 117
Instructor: Thomas Richardson
Construction of causal hypotheses. Theories of causation, counterfactuals, intervention vs. passive observation. Contexts for causal inference: randomized experiments; sequential randomization; partial compliance; natural experiments, passive observation. Path diagrams, conditional independence, and d-separation. Model equivalence and causal under-determination. Prerequisite: course in statistics, SOC 504, SOC 505, SOC 506, or equivalent; recommended: CS&SS 505, CS&SS 506, or equivalent.
Offered: jointly with STAT 566.

CS&SS 567
Statistical Analysis of Social Networks (4)
Day: MWF
         T (Lab is optional)
Time: 10:30-11:20am
Room: SAV 166
         10:30-11:20am MWF SAV 166
         9:30-10:20am T PDL C301 (Lab is optional)
Instructor: Peter Hoff
Statistical and mathematical descriptions of social networks. Topics include graphical and matrix representations of social networks, sampling methods, statistical analysis of network data, and applications. Prerequisite: SOC 504, SOC 505, SOC 506, or equivalent; recommended: CS&SS 505; CS&SS 506.
Offered: jointly with STAT 567

CS&SS 569
Visualizing Data (4)
Day: TTh
Time: 4:30-5:50pm
Room: SAV 264
Instructor: Chris Adolph
Explores techniques for visualizing social science data to complement graduate training methods. Emphasis on principles and perception of visualization, novel exploration and presentation of data and statistical models, and implementation of recommended techniques in statistics packages. Prerequisite: SOC 504, SOC 505, and SOC 506; recommended: CS&SS 505 and CS&SS 506.

CS&SS 590
CSSS Seminar (1, max. 20)
Day: W
Time: 12:30-1:20pm
Room: SAV 409
Instructor: Jeff Arnold
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.