BIOST 511
Medical Biometry I. Hughes. Data description and elementary parametric and nonparametric statistical analysis. Examples are drawn from the biomedical literature, and real data sets are analyzed by the students after a brief introduction to the use of standard statistical computer program packages. Statistical techniques covered include description of samples, comparison of two sample means and proportions, simple linear regression and correlation.
BIOST 515
Biostatistics II. Wakefield. Mathematically sophisticated introduction to linear models; multiple regression, correlation; residual analysis; dummy variables; analysis of covariance; one-, two-way analysis of variance; randomized blocks; fixed, random effects (repeated measures, factorial designs); multiple comparisons. Matrix algebra required. Real biomedical data sets analyzed. Prerequisites: 514.
BIOST 533
Classical Theory of Linear Models. Introduction to one-, two-way analysis of variance, randomized blocks; fixed, random effects, multiple comparisons. Statistical distribution theory for quadratic forms of normal variables. Fitting of the general linear model by least squares. Prerequisites: 513, STAT 421, or 423; and STAT 513; and a course in matrix algebra.
COM 517
Survey Research (5) Faculty-directed project in survey research in which basic principles of survey design, including sampling, observation, measurement, data analysis, and data interpretation, are all applied. Prerequisite: elementary statistics or permission of instructor.
COM 520
Statistical Methods in Communication (5) Reviews the steps taken in social scientific research on communication, with emphasis on the conceptualization, operationalization, and analysis of quantifiable variables. Highlights understanding of computer application of univariate and bivariate statistics, focusing on both parametric and nonparametric tests.
COM 521
Advanced Statistical Methods in Communication (4) Discusses complexities in quantitative research on communication. Focus on multivariate data design and analysis, including multiple and logistic regression, ANOVA and MANOVA, and factor analysis. Prerequisite: COM 520.
ECON 482
Econometric Methods. Startz. Application of statistical modeling to empirical work in economics. A mixture of theory and applied computer work. Primary focus is regression analysis. Prerequisite: ECON 300; ECON/STAT 311.
ECON 483
Applied Econometric Modeling. Provides undergraduates the opportunity to learn econometric model building for a particular problem while applying the theory learned in various courses to specific economic cases. Students estimate, test, and forecast economic models. Extensive use of the computer and econometric programs. Prerequisite: ECON 301; ECON/STAT 311.
ECON 580
Econometrics I. Introduction to Mathematical Statistics. 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.) Prerequisite: STAT/ECON 311; either MATH 129, MATH 136, or MATH 126 with either MATH 308 or MATH 309. Offered: jointly with STAT 481. (Staffed by Statistics). Required for majors.
ECON 583
Econometric theory I. Parks. Linear and nonlinear regression; asymptotic theory; bootstrapping.
ECON 585
Applied microeconometrics. Rose. Analysis of panel data; limited and qualitative dependent variables.
EDPSY 490
Basic Educational Statistics Estimation, testing, correlation, ANOVA. Required for majors.
EDPSY 492
Introduction to Educational Measurement. Required for majors.
EDPSY 575
Structural Equation Models Abbott. Multiple indicators, confirmatory factor analysis, latent growth curve analysis.
EDPSY 576
Hierarchical Linear Models Abbott. Nested data, multi-level models, latent growth curves.
EDPSY 592
Advanced Educational Measurement Measurement theory, measurement error, reliability, validity, for educational tests.
EDPSY 593
Experimental Design and Analysis Klockers. Experimental design with emphasis on analysis of variance.
EDPSY 594
Advanced Correlational Techniques Abbott. MANOVA, general linear model, principal components, exploratory factor analysis.
EDPSY 595
Item Response Theory IRT and binomial test theory models of educational measurement.
GEOG 526
Advanced Quantitative Methods in Geography Withers, Morrill. (1) event history analysis, (2) advanced quantitative methods (factor analysis, principal components, small-area analysis, log linear models, discrete time hazard models). This will not be offered every year.
PB AF 527
Quantitative Analysis; Quantitative Analysis for Public Managers (3) Introduces quantitative methods in the context of public management and policy analysis. Covers descriptive statistics, hypothesis testing, linear models, and research design and modeling. Helps students become knowledgeable consumers of empirical evidence. Prerequisite: graduate status in School of Public Affairs or permission of instructor. Offered yearly: Winter.
PB AF 528
Quantitative Analysis; Quantitative Analysis for Public Managers (3) Introduces quantitative methods in the context of public management and policy analysis. Covers descriptive statistics, hypothesis testing, linear models, and research design and modeling. Helps students become knowledgeable consumers of empirical evidence. Prerequisite: PB AF 527. Offered yearly: Spring.
PB AF 529
Quantitative Applications in Public Affairs (3)
POLS 491
Political Research Design and Analysis Smith. Major quantitative methods in political science, emphasizing design, data collection, data analysis, and use of computers. Requred for majors. Offered yearly.
POL S 492
Advanced Political Research Design and Analysis Ward. Testing theories, current topics in methods and statistics. Required for majors. Offered yearly.
SOC 424
Basic Applied Statistics Kuo. Sampling distributions, estimation, testing, tables, linear relationships. Required for majors.
SOC 425
Applied Statistics Warren. Multiple regression, ANOVA, ANCOVA; introductions to logistic regression, event history analysis, path analysis. Required for majors.
SOC 426
Methodology: Quantitative Techniques in Sociology. Raftery. Applied regression analysis with emphasis on interactive computer graphics techniques and interpretation. Required for majors.
SOC 526
Log-linear and Logistic Regression Models. Raftery, Kim, Herting.
SOC 536
Causal Approach to Theory Building and Data Analysis Kuo, Matsueda, Herting. Structural equations course.
SOC 528
Seminar on Selected Statistical Problems in Social Research: (1) Event history analysis (Raftery), (2) Models for longitudinal data (Herting).
SOCWF 587
Fundamentals of Social Work Statistics I. Descriptives, probability distributions, statistical inference, ANOVA, correlation and regression. Required for majors.
SOCWF 588
Fundamentals of Social Work Statistics II. Multiple regression, ANOVA, ANCOVA. Required for majors.
STAT 361
Statistics for Social Scientists Measurement, descriptives, exploratory, probability distributions, two sample tests, correlation, bivariate and multiple regression, time series, ANOVA, ANCOVA. Prerequisite: STAT/ECON 311 or STAT 220.
STAT 421
Applied Statistics and Experimental Design. Computer-aided data analyses using comparisons between batches, analysis of variance, and regression. Assumptions, data transformation, reliability of statistical measures (jackknife, bootstrap). Fisher-Gosset controversy. Prerequisite: either STAT 220, STAT 301, STAT/ECON 311, STAT 341, STAT 361, STAT/MATH 390, or
STAT/ECON 481.
Offered Fall.
STAT 423
Applied Regression and Analysis of Variance. Regression analysis, estimation, including two-stage least squares. Guided regression, building linear models, selecting carriers. Rgression residuals, ANOVA, factorial designs, response surface methods, nonparametric regression. Prerequisite: either STAT 342, STAT/MATH 390, STAT 421, or STAT 481. Offered Winter.
STAT 427
Introduction to Analysis of Categorical Data Lunneborg. Log-linear models, logistic regression, ordered response categories. Prerequisite: either STAT 342, STAT 362, or STAT 421. Offered alternate years with 428.
STAT 428
Multivariate Analysis for the Social Sciences Lunneborg. Regression, MANOVA, discriminant analysis, principal components, factor analysis. Prerequisite: either STAT 342, STAT 362, or STAT 421. Offered alternate years with 427.
STAT 512
Statistical Inference Random variables, estimation, hypothesis testing, contingency tables, confidence intervals, invariance. Prerequisite: 395 and 421, 423, or BIOST 511.
STAT 533
Classical theory of linear models Emerson. ANOVA, randomized blocks, fixed & random effects, multiple comparisions, statistical distribution theory for quadratic forms of normal variables, least squares estimation. Prerequisite: 421 or 423; and 513 (BIOSTAT 513), and a course in matrix algebra. Offered jointly with BIOST 533.
STAT 536
Log-linear modeling and logistic regression for the social sciences: log linear models and logistic regression with applications to social mobility, educational opportunity, assortative mating. Applied and computing focus. Prerequisite: 395 or SOC 425. Offered jointly with SOC 536.
STAT 570
Advanced applied statistics and linear models Murua, Lumley. Generalized linear models, REML in mixed models for randomized blocks, split plots, and longitudinal data. Generalized estimating equations, empirical model building, cross-validation, recursive partitioning, generalized additive models, projection pursuit. Prerequisite: 513; 533 or 421 and 423, matrix algebra for 570. Joint with BIOSTAT 570-572.
STAT 573
Statistical methods for categorical data: Advanced topics in generalized linear models and the analysis of categorical data: overdispersion, quasi-likelihood, parameters in link and variance functions, exact conditional inference, random effects, saddlepoint approximations. Prerequisite: 571 and 582. Offered jointly with BIOST 573. Offered alternate years.
STAT 591
Special topics in statistics. Topics of current research interest. Recent offerings include: applications of empirical process theory; environmental statistics; graphical markov models; mathematical communication; mieoses, pedigrees and populations, spatial statistics.
QERM 550
Applied Ecological Modeling. Ford. Methods of applied ecological modeling at individual, community, and ecosystem levels. Analysis of ecological problems suitable for modeling and assessment of models.
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