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CSSS Course List 2014-15

UW Course Descriptions and Time Schedule

CSSS Course Catalog

Spring Quarter 2015

CS&SS 221  
Statistical Concepts and Methods for the Social Sciences (5) NW, QSR
Time: 9:30-10:20am (MWF)
Room: SAV 260
         8:30-9:20am   (TTh) (QZ AA) THO 202
         9:30-10:20am (TTh) (QZ AB) THO 202
         8:30-9:20am   (TTH) (QZ AC) THO 211
         9:30-10:20am (TTh) (QZ AD) THO 325
         8:30-9:20am   (TTh) (QZ AE) THO 235
         9:30-10:20am (TTh) (QZ AF) THO 134
Instructor: Patricia Martinkova
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 503
Advanced Quantitative Political Methodology (5)
Day: TF
Time: 4:30-7:20pm
Room: T 4:30-7:20pm  SAV 140
          F 1:30-3:20pm  SMI 220
Instructor: Jeffrey Arnold
Theory and practice of likelihood inference. Includes 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 507
Methodology: Quantitative Techniques in Sociology (3)
Day: TTh
Time: 1:30-3:20pm
Room: DEN 313              
Instructor: Tyler 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 508
Introduction to R for Social Scientists (1)
Day: W
Time: 3:30-5:20pm
          T 3:30-4:20pm  
          Note: Optional lab on Tuesdays
Room: SAV 117   
Instructor: Aaron Erlich
Familiarizes students with the R environment for statistical computing (http://www.r-project.org). R is a freely available, multi-platform, and powerful program for analysis and graphics similar to S-PLUS. Covers the basics of organizing, managing, and manipulating social science data; basic applications; introduction to programming; links to other major statistical packages. Credit/no-credit only
CS&SS 527
Survey Research Methods (4)
Day: MW
Time: 10:30-11:50am
Room: HSR RR134
Instructor: Ali Mokdad
Provides students with skills in questionnaire development and survey methods. Students develop a questionnaire and design a survey research proposal on a health-related or social topic. Prerequisite: either HSERV 511/HSERV 513; BIOST 517/BIOST 518; or EPI 512/EPI 513, which may be taken concurrently, or permission of instructor. Students should have a survey project in mind. Offered: jointly with G H 533/HSERV 527.
CS&SS 529
Sample Survey Techniques (3)
Day: TTh
Time: 10:30-11:50am
Room: LOW 105            
Instructor: Jonathan Wakefield
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. Prerequisite: either STAT 421, STAT 423, STAT 504, QMETH 500, BIOST 511, or BIOST 517, or equivalent; or permission of instructor. Offered: jointly with BIOST 529/STAT 529.
CS&SS 560
Hierarchical Modeling for the Social Sciences (4)
Day: MWThF
Time: 2:30–3:20pm
Room: MWF 2:30-3:20pm    EEB 042
           2:30-3:20pm    SAV 121
Instructor: Brian Leroux
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. Prerequisite: SOC 504, SOC 505, SOC 506 or equivalent. Offered: jointly with SOC 560/STAT 560
CS&SS 564
Bayesian Statistics for the Social Sciences (4)
Day: TTh
Time: 10:30–11:50am
Room: TTh 10:30-11:50am   CDH 115
          Th   1:30 – 2:20pm     LOW 222
Instructor: Adrian Dobra
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. Prerequisite: SOC 504, SOC 505, SOC 506 or equivalent. Offered: jointly with STAT 564.
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.
CS&SS 594
Time Series and Panel Data for the Social Sciences
Day:     TTh
Time: 4:30-5:50pm
Room: T 4:30-5:50pm SAV 130
          Th 10:00-10:50am SAV 117
          Note: Lab on Thursdays
Instructor: Christopher Adolph
TA: Daniel Yoo
A survey of regression models for time series and time series cross-sectional data. Emphasis on modeling dynamics and panel structures with continuous outcomes, as well as on interpretation and fitting of models.  Topics vary and may include trends and seasonality, ARIMA models, lagged dependent variables, distributed lags, cointegration and error correction models, fixed and random effects, panel heteroskedasticity, missing data imputation, and causal inference using panel data.