5: Graduate School of Arts and Sciences

General Information | Programs and Degrees Offered | Admission Information
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Requirements for Specific Graduate Degrees | Departments and Programs | Faculty

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Division of Statistics
Course Descriptions | Division Degree Requirements

Course Descriptions

STAT 501 - (3) (Y)
Statistical Computing and Graphics

Prerequisites: STAT 110 or MATH 112, and graduate standing or permission of instructor. Students who have received credit for STAT 301 may not take STAT 501 for credit
An introduction to statistical computing using S-PLUS. Topics include descriptive statistics for continuous and categorical variables, methods for handling missing data, basics of graphical perception, graphical displays, exploratory data analysis, the simultaneous display of multiple variables. Students should be experienced with basic text-editing and file manipulation on either a PC or a UNIX system, and with either a programming language (e.g., BASIC) or a spreadsheet program (e.g., MINITAB or EXCEL). Credit earned in this course cannot be applied toward a graduate degree in statistics.

STAT 512 - (3) (Y)
Applied Linear Models

Prerequisite: MATH 312 or MATH 510, or permission of instructor; corequisite: STAT 598
Topics include linear regression models, inferences in regression analysis, model validation, selection of independent variables, multicollinearity, influential observations, autocorrelation in time series data, polynomial regression, nonlinear regression, and other topics in regression analysis.

STAT 513 - (3) (Y)
Applied Multivariate Statistics

Prerequisites: MATH 351 and MATH 312 or MATH 510, or permission of instructor; corequisite: STAT 598
Topics include matrix algebra, random sampling, multivariate normal distributions, multivariate regression, multivariate analysis of variance, principal components, factor analysis, and discriminant analysis. Statistical software, e.g. SAS or S-PLUS, are utilized.

STAT 514 - (3) (Y)
Survival Analysis and Reliability Theory

Prerequisite: MATH 312 or MATH 510, or permission of instructor; corequisite: STAT 598
Topics include lifetime distributions, hazard functions, competing-risks, proportional hazards, censored data, accelerated-life models, Kaplan-Meier estimator, stochastic models, renewal processes, Bayesian methods for lifetime, and reliability data analysis.

STAT 516 - (3) (E)
Experimental Design

Prerequisite: MATH 312 or MATH 510, or permission of instructor; corequisite: STAT 598
Introduction to the basic concepts in experimental design, analysis of variance, multiple comparison tests, completely randomized design, general linear model approach to analysis of variance, randomized block designs, Latin square and related designs, completely randomized factorial design with two or more treatments, hierarchical designs, split-plot and confounded factorial designs, and analysis of covariance.

STAT 517 - (3) (O)
Applied Time Series

Prerequisite: MATH 312 or MATH 510, or permission of instructor; corequisite: STAT 598
Study of the basic time series models in both the time domain (ARMA models) and the frequency domain (spectral models), emphasizing application to real data sets.

STAT 518 - (3) (SI)
Numerical Methods in Statistics

Prerequisites: MATH 351 and knowledge of a programming language suitable for scientific computation, or permission of instructor
Study of selected topics in linear algebra and related numerical algorithms of special importance in statistics, including linear least-squares, eigenvalues and eigenvectors, QR decomposition, singular value decomposition, and generalized matrix inverses.

STAT 519 - (3) (Y)
Introduction to Mathematical Statistics

Prerequisite: MATH 312 or MATH 510, or permission of instructor
Study of the fundamentals of statistical distribution theory, moments, transformations of random variables, point estimation, hypothesis testing, and confidence regions.

STAT 520 - (3) (O)
Design and Analysis of Sample Surveys

Prerequisites: MATH 112 or MATH 312, and graduate standing or permission of instructor
Discusses the main designs and estimation techniques used in sample surveys, including simple random sampling, stratification, cluster sampling, double sampling, post-stratification, ratio estimation, non-response problems, and measurement errors. Many properties of sample surveys are developed through simulation procedures. Uses the SUDAAN computer package for analyzing sample surveys. Students who have received credit for STAT 313 may not take STAT 520 for credit.

STAT 531 - (3) (Y)
Design and Conduct of Clinical Trials

Prerequisite: MATH 312, or permission of instructor
Study of experimental designs for randomized clinical trials, sources of bias in clinical studies, informed consent and other ethical issues, logistics, and interim monitoring procedures (group, sequential, and Bayesian methods).

STAT 540 - (3) (SI)
Actuarial Statistics

Prerequisite: MATH 312 or MATH 510, or permission of instructor
Covers the main topics required by students preparing for the examinations in actuarial statistics, set by the American Society of Actuaries. Topics include life tables, life insurance and annuities, survival distributions, net premiums and premium reserves, multiple life functions and decrement models, valuation of pension plans, insurance models, benefits, and dividends.

STAT 541 - (3) (Y)
Actuarial Risk Theory

Prerequisite: MATH 311 or APMA 310 or permission of instructor
Development of the basics for actuarial risk theory beginning with the economics of insurance, and uses utility theory, to illustrate why a risk-averse individual would purchase insurance. Insurance models are presented and applied to calcula to the probability of ruin, as a function case reserve, the portfolio of policies, etc. Includes a discussion of both individual (classical) and collective (modern) risk theory. The material covered is that required for the Society of Actuaries (SOA) Exam 151: Actuarial Risk Theory.

STAT 598 - (1) (Y)
Applied Statistics Laboratory

Corequisite: Enrollment in a 500-level STAT applied statistics course
Serves as the laboratory component of the division's applied statistics program. Explores the use of computer packages in data analysis. Enrollment in STAT 598 is required for all students in the division's 500-level applied statistics courses (STAT 512, 513, 514, 516, 517). STAT 598 may be taken repeatedly provided that a student is enrolled in at least one of these 500-level applied courses. However, no more than one unit of STAT 598 may be taken in any semester.

STAT 599 - (3) (IR) Topics in Statistics
Prerequisite: Permission of instructor
A study of topics in statistics that are not part of the regular course offerings.

STAT 711 - (3) (Y)
Foundations of Statistics

Prerequisite: STAT 519, or permission of instructor
Introduces the fundamental principles of statistics and applies them to practical problems. Discusses principles such as sufficiency, ancillarity, conditionality, and likelihood.

STAT 712 - (3) (E)
Statistical Inference

Prerequisite: STAT 711, or permission of instructor
A rigorous mathematical development of the principles of statistics. Covers point and interval estimation, hypothesis testing, asymptotic theory, Bayesian statistics, and decision theory from a unified perspective.

STAT 713 - (3) (Y)
Generalized Linear Models

Prerequisites: STAT 512 and STAT 519, or permission of instructor
Topics include the origins of generalized linear models, classical linear models, probit analysis, logit models for proportions, log-linear models for counts, inverse polynomial models, binary data, polytomous data, quasi-likelihood models, and models for survival data.

STAT 714 - (3) (O)
Multivariate Statistical Analysis

Prerequisites: STAT 513 and STAT 519, or permission of instructor
Topics include multivariate normal distributions, maximum likelihood inference, invariance theory, sample correlation coefficients, Hotelling's T-squared statistic, Wishart distributions, discriminant analysis, and multivariate analysis of variance.

STAT 715 - (3) (E)
Non-Parametric Statistical Analysis

Prerequisites: STAT 519 and one of STAT 512, 513, 514, 516, 517; or permission of instructor
Topics include order statistics, distribution-free statistics, U-statistics, rank tests and estimates, asymptotic efficiency, Bahadur efficiency, M-estimates, one- and two-way layouts, multivariate location models, rank correlation, and linear models.

STAT 718 - (3) (O)
Sample Surveys

Prerequisites: STAT 519, or permission of instructor
Design and analysis of sample surveys. Topics include simple random sampling, stratified sampling, multistage (cluster) sampling, double sampling, and ratio and regression estimates. Theoretical discussions supplemented by computer simulated surveys, and studies of the documentation of on-going government sample surveys.

STAT 719 - (3) (SI)
Statistical Computing

Prerequisites: STAT 512 and STAT 518, or permission of instructor
Study of computational methods for multiple linear regression, unconstrained optimization and non-linear regression, model-fitting based on Lp norms and other criteria, and robust estimation.

STAT 720 - (3) (Y)
Advanced Probability Theory for Applied Scientists

Prerequisites: MATH 531, or permission of instructor
Study of the techniques important for applied statisticians and applied scientists, including various forms of convergence for random variables, central limit theorems, asymptotics for a transformation of a sequence of random variables, and an introduction to martingales.

STAT 721 - (3) (O)
Advanced Linear Models

Prerequisites: STAT 512, STAT 513, STAT 519, or permission of instructor
Review of matrix theory (various types of generalized inverses and their properties). Topics include the theory and analysis of fixed-effects linear models; estimation of variance components in random and mixed-effects linear models; various methods of estimation of variance components, including Henderson's three methods, MLE, RMLE, MINQUE (and its modifications); and the theory and analysis of random and mixed-effects models.

STAT 731 - (3) (O)
Advanced Data Analysis

Prerequisites: STAT 512 and STAT 513, or permission of instructor
Topics include modern computer-intensive methods of data analysis, including splines and other methods of nonparametric regression, bootstrap, techniques for handling missing values and data reduction, nonlinear regression, graphical techniques, and penalized maximum likelihood estimation.

STAT 812 - (3) (Y)
Topics in Statistics

A study of current, actively researched topics in statistics.

STAT 817 - (3) (SI)
Advanced Time Series

Prerequisites: STAT 517 and MATH 736, or permission of instructor
An introduction to stationary stochastic processes, related limit theorems, and spectral representations. Includes a asymptotic theory for estimation in both the time and frequency domains.

STAT 831 - (3) (O)
Advanced Survival Analysis

Prerequisites: STAT 514, STAT 519, STAT 720 and STAT 731; or permission of instructor. STAT 720 may be replaced by MATH 736. MATH 511 is recommended, but not required.
Topics include the Martingale theory and the counting process approach to survival analysis, asymptotic theory of the Cox and related models, censoring, competing risks, multiple events per subject, parametric survival models, advanced model diagnostics for the Cox model, time-dependent covariates, bootstrap model validation, and frailty models.

STAT 832 - (3) (SI)
Topics in Biostatistics

Prerequisite: Permission of the instructor
A study of current, actively researched topics in biostatistics.

STAT 912 - (3) (Y)
Statistics Seminar

Advanced graduate seminar in current research topics. Offerings in each semester are determined by student and faculty research interests.

STAT 995 - (1-3) (Y)
Statistical Consulting

Prerequisite: Current registration in the statistics graduate program, or permission of instructor
Introduction to the practice of statistical consultation. A combination of formal lectures, meetings with clients of the statistical consulting service, and sessions in the statistical computing laboratory.

STAT 996 - (3-9) (Y)
Directed Reading

Research into current statistical problems under faculty supervision.

STAT 997 - (3-12) (Y)
Non-Topical Research, Preparation for Doctoral Research

For doctoral research, taken before a dissertation director has been selected.

STAT 999 - (3-12) (Y)
Non-Topical Research

For doctoral research, taken under the supervision of a dissertation director.

The Statistics Colloquium   The colloquium is held weekly, with the sessions devoted to research activities of students and faculty members, and to lectures by visiting statisticians on current research interests.

Continue to: Departmental Degree Requirements
Return to: Chapter 5 Index