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Course Criteria
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0.00 Credits
No course description available.
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5.00 Credits
A critical introduction to the methods used to col data in social science: surveys, archival research, experiments, and participant observation. Evaluates “facts and findings” by understanding the strengths and weaknesses of the methods that produce them. Case based. Offered: jointly with SOC 320/STAT 320; A.
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5.00 Credits
Introduction to statistical reasoning for social scientists. Built around cases representing in-depth investigations into the nature and content of statistical and socialscience principles and practice. Hands-on approach: weekly data-analysis Fundamental statistical topics: measurement, exploratory data analysis, probabilistic concepts, distributions, assessment of statistical evidence. Offered: jointly with SOC/STAT 321; W.
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5.00 Credits
No course description available.
Prerequisite:
Separate File
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5.00 Credits
Probability, generating functions; the d-method, Jacobians, Bayes theorem; maximum likelihoods, Neyman- Pearson, efficiency, decision theory, regression, correlation, bivariate normal. (Credit allowed for only one of 390, 481, and ECON 580.) Recommended: MATH 324. Offered: jointly with ECON/STAT 481; A.
Prerequisite:
STAT/ECON 311; either MATH 136 or MATH 126 with either MATH 308 or MATH 309
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5.00 Credits
Third methods course in political research. 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.
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5.00 Credits
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.
Prerequisite:
POL S 500; POL S 501
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4.00 Credits
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. Offered: jointly with STAT 504.
Prerequisite:
either STAT 342, STAT/MATH 390, STAT 421, STAT/ECON 481, or SOC 425; recommended: MATH 308
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1.00 Credits
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. Offered: Sp.
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1.00 Credits
Familiarizes graduate students in the social sciences with modern environments for statistical computing. Provides an overview of available resources and a description of fundamental tools used in quantitative courses and doctoral research. Topics include interfaces to Web-based resources, UNIX-based computing, and major statistical packages (R, SPLUS, SAS, and SPLUS). Offered: W.
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