These course descriptions were taken directly from both the Graduate, and Undergraduate catalogs. Please consult these catalogs for further information on other Statistics courses, or for interpretations of abbreviations used in these descriptions.

Click on the Course Number for a link to the most recent home page for that course (if available).

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Statistics 309 - Introduction to Mathematical Statistics
(Crosslisted with Math) 4 cr.
Probability and combinatorial methods, discrete and continuous, univariate and multivariate distributions, expected values, moments, normal distribution and derived distributions, estimation. P: For majors in math and stats, Math 223 or 234.

Statistics 310 - Introduction to Mathematical Statistics (Crosslisted with Math) 4 cr.
Unbiased estimation, maximum likelihood estimation, confidence intervals, tests of hypotheses, Neyman-Pearson fundamental lemma, likelihood ratio test, applications to general linear model and analysis of variance, categorical data analysis, nonparametric methods. P: For majors in Math and Stat, Math 309 or Stat 309.

Statistics 351 - Introductory Nonparametric Statistics 3 cr.
Distribution free statistical procedures or methods valid under nonrestrictive assumptions: basic tools; counting methods; order statistics, ranks; distribution free tests and associated interval and point estimators; sign test; signed rank tests; rank tests; Mann Whitney Wilcoxon procedures; Kolmogorov Smirnov tests; permutation methods; methods for discrete data with zeros and ties; computer techniques and programs; discussion and comparison with parametric methods. P: Stat 201 or 301 or 224 or cons inst.

Statistics 411 - An Introduction to Sample Survey Theory and Methods 3 cr.
An elementary development of the statistical theory (and methods) used to design and analyze the results from sample surveys. Topics: basic tools, simple random sampling, ratio and regression estimation, stratification, systematic sampling, cluster (area) sampling, unequal probability sampling, sampling on successive occasions, non-sampling errors, analytical sample surveys. For illustration and clarification, examples drawn from diverse areas of application. P: Stat 224, 201, 301 or an equiv intro statistics course.

Statistics 421 - Applied Categorical Data Analysis 3 cr.
Methods of analyzing multidimensional contingency tables, emphasis on practical applications. The use of computing packages for analysis of such data. Model selection, testing goodness of fit, estimation of parameters, measures of association and methods for detecting sources of significance. P: Stat 301 or cons inst.

Biostatistics and Medical Informatics 541 (3 credits) - Introduction to Biostatistics - is designed for the biomedical researcher. Topics include: descriptive statistics, hypothesis testing, estimation, confidence intervals, t-tests, chi-squared tests, analysis of variance, linear regression, correlation, nonparametric tests, survival analysis and odds ratio. Biomedical applications are discussed for each topic. Prerequisites: Math 221 or equivalent or instructor's consent.

Statistics 609 - Mathematical Statistics I 3 cr.
Review of probability, random variables and vectors and their distributions, moments and inequalities, generating functions, transformations of random variables, sampling and distribution theory, convergence concepts for sequences of random variables, laws of large numbers, central limit and other limit theorems. P: Stat 309 or 431, Math 340, Math 521, or equiv or cons inst.

Statistics 610 - Introduction to Statistical Inference 4 cr.
Conditioning, distribution theory, approximation to distributions, modes of convergence, limit theorems, statistical models, parameter estimation, comparison of estimators, confidence sets, theory of hypothesis tests, introduction to Bayesian inference and nonparametric estimation. P: Stat 309 or Stat 431, Math 521, Math 340 or equiv or cons inst.

Statistics 611 - Sample Survey Theory and Method 3 cr.
Simple random sampling; stratified random sampling; ratio and regression estimates; systematic sampling; subsampling with units of equal and unequal size; double sampling; multi-stage and multi-phase sampling; Bayesian and other approaches. P: Stats 310 or equiv.

Statistics 632 - Introduction to Stochastic Processes(Crosslisted with Math, Ind Engr, OIM) 3 cr.
Markov chains: classification, recurrence, transcience, limit theory. Renewal theory, Markov processes, birth-death processes. Applications to queueing, branching, and other models in science, engineering and business. Topics drawn from semi-Markov processes, martingales, Brownian motion. P: Math 431, or Stat 309 & 310, or Stat 311 & 312, or Stat 313 or 314.

Statistics 641 - Statistical Methods for Clinical Trials 3 cr.
Statistical issues in the design of clinical trials, basic survival analysis, data collection and sequential monitoring. Intended for statistics graduate students; those with medical backgrounds should take Stat 542. P: Math/Stat 310 or equiv or cons inst.

Statistics 642 - Statistical Methods for Epidemiology 3 cr.
Methods for analysis of case-control, cross sectional, and cohort studies. Covers epidemiologic study design, measures of association, rates, classical contingency table methods, and logistic and Poisson regression. P: Stat 310 or equiv or cons inst.

Statistics 643 - Practicum in Coordinating Center Methods 3 cr.
Practicum in the operation of a coordinating center in a clinical trial or epidemiologic study. Covers organization, randomization, forms design and collection, quality control and other operational responsibilities of coordinating centers. P: Stat 641 or 642 or cons inst.

Statistics 701 - Applied Time Series Analysis, Forecasting and Control I3 cr.
Theory and application of discrete time series models illustrated with forecasting problems. Principles of iterative model building. Representation of dynamic relations by difference equations. Autoregressive integrated Moving Average models. Identification, fitting, diagnostic checking of models. Seasonal model application to forecasting in business, economics, ecology, and engineering used at each stage, which the student analyzes using computer programs which have been specially written and extensively tested. P: Stat 310 or equiv.

Statistics 702 - Applied Time Series Analysis, Forecasting and Control II 3 cr.
Further theory and application of discrete time series models illustrated by transfer function estimation, intervention analysis, and forecasting and control problems for multiple time series. Illustrations at each stage with real examples from business, economics, ecology and engineering which the student analyzes using the computer. P: Stat 701.

Statistics 709 - Mathematical Statistics (Crosslisted with Math) 4 cr.
Introduction to measure theoretic probability; derivation and transformation of probability distributions; generating functions and characteristic functions; conditional expectation, sufficiency, and unbiased estimation; methods of large sample theory including laws of large numbers and central limit theorems; order statistics. P: Cons inst or one yr adv calculus and Math, Stat 431, Math, Stat 310.

Statistics 710 - Mathematical Statistics (Crosslisted with Math) 4 cr.
Estimation, efficiency, Neyman-Pearson theory of hypothesis testing, confidence regions, decision theory, analysis of variance, and distribution of quadratic forms. P: Stat, Math 709.

Statistics 731 - Probability and Analysis 3 cr.
Abstract measure theory and theory of integration with probabilistic and statistical applications. Extension of measures, basic integration theorems, Radon-Nikodym Theorem, Fubini's Theorem. Modes of convergence of sequences of random variables and their relationships. Moment and probability inequalities. Scheff theorem for probability density functions. Slutsky theorems with some statistical applications. Helly-Bray type theorems. Conditional expectation and conditional probabilities. Convergence theorems, laws of large numbers, central limit theorems, characteristic functions, weak convergence topics. P: Cons inst.

Statistics 732 - Large Sample Theory of Statistical Inference 3 cr.
Stochastic modes of convergence. Asymptotic theory of normed sums of random variables with applications to asymptotic normality of estimators. Methods for deriving limit distributions of nonlinear statistics. Asymptotic relative efficiencies. Asymptotic confidence regions and tests of hypotheses. Models of non-identically distributed or dependent random variables. P: Either Stat 709, 731, or 831 or cons inst.

Statistics 741 - Survival Analysis Theory and Methods 3 cr.
Theory and practice of analytic methods for censored survival data, including nonparametric and parametric methods, the proportional hazards regression model, and a review of current topics in survival analysis. P: Stat 610 or 710 or equiv or cons inst.

Statistics 749 - Mathematical Models and Response Surface Methodology I 3 cr.
Two-level factorial and fractional factorial designs, applications, blocking, polynomial models, first-order designs, second-order designs, several responses, determination of optimum conditions, canonical reduction, design criteria involving variance and bias. P: Cons inst or Stat 310.

Statistics 750 - Mathematical Models and Response Surface Methodology II 3 cr.
Advanced topics in response surface methodology. P: Stat 749.

Statistics 751 - Sequential Analysis 3 cr.
Sequential tests of simple hypotheses and their optimal properties; composite hypotheses including derivation of the sequential t-test; sequential estimation; stochastic approximation, topics in sequential analysis. P: Stat 310 or equiv.

Statistics 760 - Multivariate Analysis I 3 cr.
Multivariate normal distribution, estimation of mean and covariance matrix; Wishart distribution; distribution of partial and multiple correlation coefficients; Hotelling's Tø2ø, principal components. P: Cons inst or Stat 710.

Statistics 761 - Multivariate Analysis II 3 cr. P: Stat 760.

Statistics 765 - Stochastic Models I 3 cr.
Further applications of stochastic models; renewal theory; theory of regenerative events; theory of queues; Markovian and semi-Markovian processes; models of epidemics and of accident occurrence. P: Stat 710 or cons inst.

Statistics 771 - Statistical Computing 3 cr.
The design of statistical software including special techniques for probability distributions, methods of simulation of random processes, numerical methods for linear models and multivariate analysis, and methods for nonlinear models. P: Stat 333 or equiv or cons inst.

Statistics 775 - Introduction to Bayesian Decision and Control I (Crosslisted with Econ, Gen Bus) 3 cr.
Common sampling models in business and economic problems, information from data, likelihood function of parameters, choices of models, Bayes' Theorem, subjective basis for probability, sequential nature of Bayesian inference, prior and posterior distributions of parameters in binomial, poisson, exponential and normal populations, comparison of two normal distributions, predictive distributions, decision theory, utility, risk aversion, extensive form of analysis, two-action problems, point estimation, best population problems, economics of sampling. P: Stat 309, 313, or 311 or equiv.

Statistics 803 - Experimental Design I (Crosslisted with Math) 3 cr. Summary of matrix algebra required, theory of estimable functions, incomplete blocks, balanced incomplete block designs, partially balanced incomplete block designs. P: Stats 310 or cons inst.

Statistics 804 - Experimental Design II 3 cr. P: Stat 803.

Statistics 809 - Non Parametric Statistics 3 cr.
Statistical procedures valid under unrestrictive assumptions; sign test; confidence intervals; efficiency comparisons; signed rank procedures; Walsh sums; point estimators; two sample rank tests; zeros, ties, and other problems of discrete data; order statistics; Winsorized and truncated point estimators and connection with gross error models; permutation procedures; combinatorial problems, and computer applications. P: Stat 710 or cons inst.

Statistics 824 - Nonlinear Regression Analysis with Engineering Applications 3 cr.
Engineering application of statistical design techniques; sequential design strategies; nonlinear model building; model discrimination. P: Stat 333, 424 or 849; or cons inst.

Statistics 826 - Theory of Life Testing and Reliability 3 cr.
The statistical theory of reliability and life testing. Probabilistic failure models, complete and censored data, robustness considerations, nonparametric life test procedures, system reliability, redundancy optimization and related topics, application of stochastic processes in reliability, group testing. P: Stat 710 or cons inst.

Statistics 829 - Decision Theory 3 cr.
Statistical inference and decision theory, decision functions, game theory, normal forms, extensive forms, zero sum games, the minimax theorem, sequential games, axiomatic treatment of utility, complete classes of decision functions and strategies. P: Stats 710 or cons inst.

Statistics 831 - Theory of Probability (Crosslisted with Math) 3 cr.
Measure theoretic foundations and modern analytic methods of theory of probability and stochastic processes. P: Cons inst.

Statistics 832 - Theory of Probability (Crosslisted with Math) 3 cr. Continuation of 831. P: Cons inst.

Statistics 840 - Time Series Analysis I 3 cr.
The Hilbert space spanned by a time series. Spectral representation, Karhunen-Loeve expansion. Prediction and regression in the continuous case. Signal detection, conditions for perfect detectability and discrimination. Theory of spline functions and stochastic processes, smoothing, estimation of derivatives, continuous linear functions. P: Stat 710 or cons inst.

Statistics 841 - Time Series Analysis II 3 cr.
Discrete time multivariate time series, tests of independence, estimation of transfer function, regression coefficients, asymptotic relationships between time and frequency domain analysis, the Brownian Bridge, invariance principle, weak convergence of stochastic processes. P: Stat 840.

Statistics 842 - Hypothesis Testing 3 cr.
Measure theoretic background, exponential families; uniformly most powerful tests, least favorable priors; unbiased tests, invariant tests, and applications to exponential families and the general linear hypothesis. P: Stat 710 or cons inst.

Statistics 849 - Theory and Application of Regression and Analysis of Variance I 3 cr.
Theory and applications of the general linear model; graphical methods; simultaneous inference; regression diagnostics; analysis of variance of fixed, random and mixed effects models; Ancova: violations of assumptions. P: Stat 310, 312 or 314.

Statistics 850 - Theory and Application of Regression and Analysis of Variance II. 3 cr.
Theory and applications of the general linear model; graphical methods; simultaneous inference; regression diagnostics; analysis of variance of fixed, random and mixed effects models; Ancova: violations of assumptions. P: Stat 849.

Statistics 851 - Generalized Linear Models. 3 cr.
Methods for developing, fitting and checking models beyond the classical linear model framework. Binary, ordinal and categorical models will be examined, as well as the non-Gaussian continuous case and more advanced topics. P: Stat 850 or con reg or cons inst.

Statistics 853 - Bayesian Inference 3 cr.
Sampling theory and its critique, subjective probability, likelihood principles, Bayes theorem, Bayesian analysis of Normal theory inference problems, the Behrens-Fisher problem, assessment of model assumptions, robustness of inference, analysis of variance, estimation of variance components, empirical Bayes, some aspects of multivariate problems. P: Stat 710.

Statistics 860 - Topics in Time Series and Approximation Theory
3 cr.
Topics in statistical and approximation theoretic methods of estimating functions and values of functionals from experimental data. Experimental design and data analysis problems that also arise as problems in approximation theory. Convergence theorems. P: Stat 710 or cons inst.

Statistics 992 - Seminar. 1-3 cr. Content varies. P: Cons inst.

Statistics 998 - Statistical Consulting 3 cr.
Consulting apprenticeship. P: 9 cr in statistics and cons inst.

Computer Sciences 302 - Introduction to Programming I, II, SS; 3 cr
(r-N-I). Instruction and experience in the use of an object-oriented programming language. Program design; development of good programming style; preparation for other computer science courses. P: Problem solving skills such as those acquired in a stats, logic, or adv HS algebra crse, or cons inst. Open to Fr.

Math 340 - Elementary Matrix and Linear Algebra I, II, SS; 3 cr (N-A). Matrix algebra, linear systems of equations, vector spaces, sub-spaces, linear dependence, rank of matrices, determinants, linear transformations, eigenvalues and eigenvectors, diagonalization, inner products and orthogonal vectors, symmetric matrices. P: Math 223 or 234. Credit may not be received for both Math 320 & 340.

Math 521 - Advanced Calculus I, II, SS; 3 cr (N-A).
Fundamental notions of limits, continuity, differentiation, and integration, for functions of one or more variables, convergence and uniform convergence of infinite series, and improper integrals. P: Math 340 or con reg.

Genetics 466 - General Genetics (Crosslisted with Botany, Zoology) I, II, SS; 3 cr (B-I).
Genetics in eukaryotes and prokaryotes. Includes Mendelian genetics, mapping, molecular genetics, genetic engineering, cytogenetics, quantitative genetics, and population genetics. Illustrative material includes viruses, bacteria, plants, fungi, insects, and humans. P: Algebra, 1 yr chem & 1 yr biology or cons inst.

Medical Genetics 565 - Human Genetics (Crosslisted with MdGenet) 3cr.
Principles, problems, and methods of human genetics. Surveys aspects of medical genetics, biochemical genetics, molecular genetics, cytogenetics, quantitative genetics, and variation as applied to humans. P: Genet 466 or equiv or consinst.

Medical Genetics 629 - Population Genetics (Crosslisted with Genetics) 3cr.
Introduction to field of theoretical population genetics with emphasis on mathematical modeling. P: Gen 466 or equiv & courses in calc and statistics.

Oncology 401 - Introduction to Experimental Oncology 2 cr.
Biological processes associated with and characteristic of neoplasia. P: Biol & org chem or cons inst.

Physiology 603 -

Preventive Medicine 797 - Introduction to the Strategy and Methods of Epidemiology 2-3 cr.
Lectures and discussions on design, implementation and interpretation of epidemiologic studies; emphasis on methodologic problems in the measurement of disease frequency, natural history and risk factors. P: Grad st in clinical/life science or cons inst.