Chairman: G. Casella. Graduate Coordinator: J. G. Booth. Distinguished Professor: A. G. Agresti; M. Ghosh. Professors: J. G. Booth; R. L. Carter; M. N. Chang; J. A. Cornell; A. I. Khuri; R. C. Littell; R. G. Marks; F. G. Martin; R. H. Randles; P. V. Rao; A. Rosalsky; R. L. Scheaffer; J. J. Shuster; D. D. Wackerly; M. C. K. Yang. Associate Professors: M. Conlon; J. P. Hobert; J. Kepner; K. M. Portier; B. Presnell. Assistant Professors: M. Devidas; J. G. Booth;A. Hutson; W. London; R. Natarajan; P. Ohman; S. Wu.
Graduate programs are available leading to Master of Science in Statistics, Master of Statistics, and Doctor of Philosophy degrees. Both master's programs usually require two years of course work including material covered in STA 6207, STA 6208, STA 6209, STA 6326, STA 6327, STA 6246 and MAA 6236. Students wishing an emphasis in biostatistics are not required to take STA 6209 but must take STA 6176, 6177. In addition to passing the master's comprehensive examination, requirements for the Ph.D. degree include STA 6466, STA 6467, STA 7346, and STA 7347.
Co-Major—The Department offers a new co-major program in conjunction with the Fisher School of Accounting leading to the Doctor of Philosophy degree in statistics and business administration—accounting. For information on this program, consult the departmental graduate coordinator.
STA 5106—Computer Programs in Statistical Analysis (1) Prereq: STA 6166. Utilization of library computer programs for analysis of balanced experimental data and regression analysis.
STA 5156—Industrial Statistical Methods (3) Prereq: STA 3032, STA 4322, or STA 6166. Design and analysis methods for industrial experiments, including response surface methods, factorial, fractional factorial, Plackett-Burman, and central composite designs. Use and design of control charts.
STA 5223—Applied Sample Survey Methods (3) Prereq: STA 2023, STA 2122, STA 4322, STA 6126, or STA 6166. Design and analysis of sample surveys. Sources of error; questionnaire design; simple random, stratified, systematic, and cluster sampling; plus practical application of concepts.
STA 5325—Mathematical Methods of Statistics (3) Prereq: MAC 2313 or equivalent. Topics in probability and statistics, particularly discrete and continuous random variables, sampling distributions, estimation, and hypothesis testing. Applications to engineering and natural science.
STA 5328—Mathematical Methods of Statistics II (3) Prereq: STA 5325 or equivalent. Mathematical foundations of point estimation, confidence intervals, tests of hypotheses, linear models, and analysis of variance.
STA 5503—Categorical Data Methods (3) Prereq: STA 3024, STA 3032, STA 4210, STA 4322, STA 6127, or STA 6167. Intended for graduate students not majoring in statistics. Description and inference using proportions and odds ratios, multi-way contingency tables, logistic regression and other generalized linear models, and loglinear models applications.
STA 5507—Applied Nonparametric Methods (3) Prereq: STA 2023, STA 3032, STA 4210, STA 4322, STA 6126, STA 6166. Introduction to nonparametric statistics, including one and two sample testing and estimation methods, one- and two-way layout models, and correlation and regression models.
STA 5701—Applied Multivariate Methods (3) Prereq: STA 3024, STA 4322, STA 6127, STA 6166, or STA 4211. Review of matrix theory, univariate normal, t, chi-squared and F distributions, and multivariate normal distributions. Inference about multivariate means, Hotelling's T2, multivariate analysis of variance, multivariate regression, and multivariate repeated measures. Inference about covariance structure, principal components, factor analysis, and cannonical correlation. Multivariate classification techniques, discriminant and cluster analysis. Additional topics at discretion of instructor, time permitting.
STA 5823—Stochastic Process Methods (3) Prereq: STA 4321 or STA 5325. Mathematical foundations of elementary stochastic processes, including Poisson processes and Markov chains, branching, and renewal processes.
STA 6092—Applied Statistical Practice (3) Prereq: STA 6207, STA 6208, STA 6209. Introduction to communication, management, organizational, computational, and statistical thinking skills necessary to consulting in statistics. Integration of graphical and numerical computing tools, research design concepts, data summary and statistical inference methods.
STA 6126—Statistical Methods in Social Research I (3) Descriptive statistics, estimation, significance tests, two-sample comparisons, methods for nominal and ordinal data, regression and correlation, introduction to multiple regression.
STA 6127—Statistical Methods in Social Research II (3) Prereq: STA 6126. Further topics in multiple regression, model building, analysis of variance, analysis of covariance, multivariate analysis of categorical data.
STA 6166—Statistical Methods in Research I (4) Statistical inference based on t, F, and C2 tests. Analysis of variance for basic experimental designs. Factorial experiments. Regression analysis and analysis of covariance.
STA 6167—Statistical Methods in Research II (4) Prereq: STA 6166. Analysis of split-plot and nested designs with incomplete blocks, confounding and fractional replications. Analysis of count data. Nonparametric methods.
STA 6176—Introduction to Biostatistics (3) Prereq: STA 6207, STA 6327. Analysis of epidemiological studies, measures of morbidity and mortality, methods for rates and proportions, bioassay, longitudinal data analysis.
STA 6177—Advanced Topics in Biostatistics (3) Prereq: STA 6327. Survival analysis, Kaplan-Meier estimates, proportional hazards model, related tests, phase I, II, and III clinical trials, designs and protocols.
STA 6178—Genetic Data Analysis (3) Prereq: STA 6327. Biological and molecular basis. Likelihood ratio test, multinomial distribution and Bailey's theorem. Linkage analysis of qualitative traits. Twin and sibling studies. Computation of kinship coefficient by matrix method. Mapping of quantitative trait loci by EM algorithm. Heritability. Breeding value prediction using flanking markers with variance component analysis. Linkage disequilibrium analysis for gene mapping. Forensic genetics using Bayes' formula. Genetic counseling. Gene pattern matching and construction of evolutionary trees by cluster analysis.
STA 6200—Fundamentals of Research Design (2) Choosing the research objective, determining the type of data to collect, repeated measures and blocking, choosing the sample and the randomization technique, designing a data collection form. Applications to biomedical data.
STA 6201—Analysis of Research Data (3) Prereq: STA 6200. Introduction to the most commonly used statistical analyses for evaluating research data, with application to the biomedical sciences. Emphasis on choosing the appropriate procedure and evaluating the results properly, rather than on the computational aspects of the procedures.
STA 6207—Applied Statistical Methods (3) Prereq: STA 4322. Overview of normal theory inference, nonparametric, and categorical data methods; basic concepts of experimental design; analysis of variance; introduction to factorial and nested experiments.
STA 6208—Regression Analysis (3) Prereq: STA 6207. Simple linear regression; multiple regression; model selection residual analysis; influence diagnostics; multicollinearity; ANOVA and regression; generalized linear models; nonlinear regression.
STA 6209—Design and Analysis of Experiments (3) Prereq: STA 6207. Tests of assumptions; block designs; control of two-way heterogeneity; cross over designs; factorial experiments; fractional factorials; analysis of "messy" data.
STA 6226—Sampling Theory and Application (3) Prereq: STA 6327 or consent of instructor. Theory and application of commonly used sampling techniques; simple random sample, cluster, ratio, regression, stratified, multistage, and systematic samples. Special topics include wildlife surveys, non-sampling error adjustment, categorical data analysis, and practical survey examples.
STA 6246—Theory of Linear Models (3) Prereq: STA 6208, STA 6327, STA 6329. Theory for analysis of linear models in univariate data; distributions of quadratic forms; full rank linear models; fixed effect models of less than full rank; balanced random and mixed models; unbalanced random and mixed models.
STA 6247—Advanced Topics in Design and Analysis (3) Prereq: STA 6246, STA 6207-STA 6209. First and second order response surface designs and models. The objectives of a response surface investigation. The determination of optimum conditions for response surface models. The integrated mean square error criterion for the choice of a design. Minimum bias estimation designs. The analysis of multiresponse experiments. Designs for nonlinear models. Some advanced topics in unbalanced mixed models.
STA 6248—Advanced Topics in Linear Models (3) Prereq: STA 6209, STA 6246. Estimation of variance components. Best linear unbiased prediction of random effects. Measures of imbalance. Exact tests for unbalanced random and mixed-effects models. Generalized P-values.
STA 6326—Introduction to Theoretical Statistics I (3) Prereq: MAC 2313. Theory of probability. Probability spaces, continuous and discrete distributions, functions of random variables, multivariate distributions, expectation, conditional expectation, central limit theorem, useful convergence results, sampling distributions, distributions of order statistics, empirical distribution function.
STA 6327—Introduction to Theoretical Statistics II (3) Prereq: STA 6326. Estimation and hypothesis testing. Sufficiency, information, estimation, maximum likelihood, confidence intervals, uniformly most powerful tests, likelihood ratio tests, sequential testing, univariate normal inference, decision theory, analysis of categorical data.
STA 6329—Statistical Applications of Matrix Algebra (2) Prereq: MAC 2313, STA 6208. Basic theory of determinants, inverses and generalized inverses, eigenvalues and eigenvectors; applications of partitioned matrices; diagonalization and decomposition theorems; applications in least squares.
STA 6466—Probability Theory I (3) Prereq: MAA 5228, STA 6236, or equivalent. Measure and probability spaces; random variables; distribution functions; abstract Lebesgue and Stieltjes integration; monotone; dominated, Cauchy, and mean convergence; Fubini and Radon-Nikodym theorems; zero-one laws.
STA 6467—Probability Theory II (3) Prereq: STA 6466. Summability of independent random variables, laws of large numbers, convergence in distribution, characteristic functions, uniqueness and continuity theorems, the Lindeberg-Feller central limit theorem, degenerate convergence criterion.
STA 6505—Analysis of Categorical Data (3) Prereq: STA 6327 and STA 6207 or consent of instructor. Varieties of categorical data, cross-classification tables, tests for independence. Measures of association. Loglinear models for multi-dimensional tables. Logit models and analogies with regression. Specialized methods for ordinal data.
STA 6526—Nonparametric Statistics (3) Prereq: STA 6327 or consent of instructor. Inference based on rank statistics—one, two and k-sample problems, correlation and regression problems and analysis of contingency tables. Conditionally distribution-free rank tests. Pitman asymptotic relative efficiency.
STA 6662—Statistical Methods for Industrial Practice (3) Prereq: STA 6207 and STA 6326; coreq: STA 6327 or consent of instructor. Statistical techniques used in modern industry, including variance components analysis, control charting, estimation of process characteristics, evolutionary operation, fraction, factorials, screening experiments.
STA 6707—Analysis of Multivariate Data (3) Prereq: STA 6208 and facility in a computer language. Techniques for analyzing multivariate data. Emphasis on MANOVA and tests on the structure of the dispersion matrix. Topics will include discriminant, factor, profile, and cluster analyses.
STA 6746—Multivariate Analysis (4) Prereq: STA 6246 or consent of instructor. Singular transformations and the generalized Jacobian. The multivariate normal distribution, Wishart distribution, and the U distribution. Distribution of the latent roots of one Wishart matrix in the metric of another. Noncentral counterparts of these distributions—an introduction to zonal polynomials. Distributions of variables constrained to lie on a sphere or a simplex. The resultant and its usage in analysis of directional data.
STA 6826—Stochastic Processes I (3) Prereq: STA 6327. Discrete time and state Markov process. Ergodic theory.
STA 6857—Applied Time Series Analysis (3) Prereq: STA 4322 and a basic computer language. Linear time series model building, spectral density estimation, analysis of nonstationary data, SAS package on Box and Jenkins model building and forecasting. Case studies in recent literature will be discussed.
STA 6900—Problems in Statistics (1-4; max: 6) Prereq: permission of department. Special problems in research methods, sampling methods, and experimental designs.
STA 6905—Individual Work (1-4; max: 10) Prereq: permission of department. Special topics designed to meet the needs and interests of individual students.
STA 6910—Supervised Research (1-5; max: 5) S/U.
STA 6934—Special Topics in Statistics (1-3; max: 8) Prereq: permission of graduate adviser.
STA 6937—Seminar: Current Topics in Statistics (1-3; max: 6) Prereq: permission of department. Discussion of current research topics in statistics not covered in regular courses. S/U.
STA 6938—Seminar (1; max: 15) Prereq: permission of department. Special topics of an advanced nature suitable for seminar treatment but not given in regular courses. S/U.
STA 6940—Supervised Teaching (1-5; max: 5) S/U.
STA 6942—Internship (1-3; max: 3) Prereq: STA 6208 or equivalent and permission of graduate coordinator. Supervised statistical consulting involving planning and/or analysis of research data. Whenever possible, student meets with researcher. Supervision by faculty member or delegated authority and post-internship report. S/U.
STA 6971—Research for Master's Thesis (1-15) S/U.
STA 7179—Survival Analysis (3) Prereq: STA 6177. Theoretical introduction to statistical inferential procedures useful for analyzing randomly right censored failure time data.
STA 7249—Generalized Linear Models (3) Prereq: STA 6207, STA 6208, STA 6327. Fitting of generalized linear models, diagnostics, asymptotic theory, overdispersion, estimating equations, mixed models, generalized additive models, smoothing.
STA 7334—Limit Theory (3) Prereq: STA 6467. Review of different models of convergence. Cramer-Wold device. Multivariate CLT. Asymptotic theory of empirical distribution and sample quantiles. Bahadur's representation. Asymptotic theory of sample moments. Delta method and its multiparameter generalization. Variance stabilizing transformation. U-statistics: asymptotic theory and its statistical applications. Hoeffding's decomposition. Asymptotic theory of maximum likelihood estimation. Wald's consistency theorem for MLE. Asymptotic normality and efficiency. Asymptotic theory of GLRTs. Statistical applications: asymptotic theory of categorical data, linear models, and generalized linear models.
STA 7346—Statistical Inference I (3) Prereq: STA 6327. Decision rules and risk functions. Sufficiency, Minimax, and Bayes rules for estimation of location and scale parameters.
STA 7347—Statistical Inference II (3) Prereq: STA 7346. Bayesian statistical inference. Inference using large samples. Relative efficiencies of tests and estimates with special reference to Pitman and Bahadur efficiencies.
STA 7506—Advanced Categorical Data Analysis (3) Prereq: STA 6327, STA 6208, STA 6505. Models for multinomial responses such as ordinal data, models for matched pairs and more complex types of repeated categorical measurement data, and small-sample and large-sample theory for parametric model fitting, and recent research in categorical data analysis.
STA 7979—Advanced Research (1-12) Research for doctoral students before admission to candidacy. Designed for students with a master's degree in the field of study or for students who have been accepted for a doctoral program. Not open to students who have been admitted to candidacy. S/U.
STA 7980—Research for Doctoral Dissertation (1-15) S/U.