Registration and Auditing of CSSS Courses for UW Students, UW Employees (Faculty, Staff, other) and Non-UW Individuals
UW Course Descriptions and Time Schedule
CSSS Course Catalog
- CS&SS 221
- Statistical Concepts and Methods for the Social Sciences (5) NW, QSR
- Day: MTWThF
- Time: 9:30-10:20am (MWF)
- Room: EEB 105
- 8:30-9:20pm (TTh) (QZ AA), DEN 302
- 9:30-10:20pm (TTh) (QZ AB), DEN 302
- 8:30-9:20pm (TTh) (QZ AC), JHN 022
- 9:30-10:20pm (TTH) (QZ AD), JHN 022
- 8:30-9:20pm (TTh) (QZ AE), LOW 201
-          9:30-10:20pm (TTH) (QZ AF), LOW 201
- Instructor: Kyle Crowder
- 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 321
- Case-based Social Statistics 1 (5) I&S, QSR
- Day: MTWThF
- Time: 10:30-11:20am
- Room: MGH 044
- 10:30-11:20am (MWF), MGH 295
- 10:30-11:20am (T), MGH 251
- 10:30-11:20am (Th), MGH 044
- Instructor: Tyler McCormick
- Introduction to statistical reasoning for social scientists. Built around cases representing in-depth investigations into the nature and content of statistical and social-science principles and practice. Hands-on approach: weekly data-analysis laboratory. Fundamental statistical topics: measurement, exploratory data analysis, probabilistic concepts, distributions, assessment of statistical evidence.
Offered jointly with SOC 321/STAT 321.
- Introduction to Mathematical Statistics: Econometrics I (5) NW
- Day: TThF
- Time: 1:30-2:50pm
- Room: JHN 075
- 1:30-2:50pm (TTh), JHN 075
- 12:30-1:20pm (F), CMU 228
- 1:30-2:20pm (F), CMU 326
- Instructor: Caren Marzban
- Prerequisites: POL S/CS&SS 501; POL S/CS&SS 503.
- Examines methods, tools, and theory of mathematical statistics. Covers, probability densities, transformations, moment generating functions, conditional expectation. Bayesian analysis with conjugate priors, hypothesis tests, the Neyman-Pearson Lemma. likelihood ratio tests, confidence intervals, maximum likelihood estimation, Central limit theorem, Slutsky Theorems, and the delta-method. (Credit allowed for only one of STAT 390, STAT 481, and ECON 580.)
Prerequisite: STAT 311/ECON 311; either MATH 136 or MATH 126 with either MATH 308 or MATH 309; recommended: MATH 324.
Offered jointly with ECON 580/STAT 509.
- CS&SS 510
- Maximum Likelihood Methods for the Social Sciences (5)
- Day: TThF
- Time: 4:30-5:50pm
- Room: SAV 264
- 4:30-5:50pm (TTh), SAV 264
- 3:30-5:20pm (F), SAV 117
- Instructor: Christopher Adolph
- Introduces maximum likelihood, a more general method for modeling social phenomena than linear regression. Topics include discrete, time series, and spatial data, model interpretation, and fitting.
Prerequisite: POL S 501/CS&SS 501; POL S 503/CS&SS 503.
Offered jointly with POL S 510.
- CS&SS 536
- Analysis of Categorical Data (3)
- Day: MWF
- Time: 2:30-3:20pm
Room: THO 325
- Instructor: Adrian Dobra
- Analysis of categorical data in the social sciences. Binary, ordered, and multinomial outcomes, event counts, and contingency tables. Focuses on maximum likelihood estimations and interpretations of results.
Prerequisite: SOC 504, SOC 505, SOC 506, or equivalent; recommended: CS&SS 505 and CS&SS 506, or equivalent. Offered jointly with SOC 536/STAT 536.
- CS&SS 589
- Multivariate Data Analysis for the Social Sciences (4, max 8)
- Day: TTh
- Time: 1:30-2:50pm
- Room: AND 010
- Instructor: Elena Erosheva
- Provides social scientists with an introduction to multivariate analysis techniques and the knowledge to carry them out. Focuses on statistical methods that explore relationships between observed variables. Topics include principal components, cluster, factor, latent class analysis.
Prerequisite: SOCWL 587, SOCWL 588, or equivalent.
Offered jointly with SOC WL 589.
- 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.