ST - Statistics


ST 101Statistics by ExampleUNITS: 3 - Mathematical Sciences
Sampling, experimental design, tables and graphs, relationships among variables, probability, estimation, hypothesis testing. Real life examples from the social, physical and life sciences, the humanities and sports. Credit not allowed if student has prior credit for another ST course


ST (PSY) 240Introduction to Behavioral Research IUNITS: 3 - Offered in Fall and Spring
Prerequisite: PSY and HRD Majors, PSY 200, Corequisite: PSY (ST) 241
Introduction to quantitative methods in psychology, including measurement, experimental control, validity, and fundamentals of research design. Discussion of distributions and statistical inference.


ST (PSY) 241Introduction to Behavioral Research I LabUNITS: 1 - Offered in Fall and Spring
Prerequisite: PSY 200, PSY and HRD Majors, Corequisite: PSY (ST) 240
Students design, analyze and report a variety of simple experiments.


ST (PSY) 242Introduction to Behavioral Research IIUNITS: 3 - Offered in Fall and Spring
Prerequisite: PSY or HRD Majors, PSY (ST) 240, Corequisite: PSY (ST) 243
Continuation of PSY (ST) 240. Ethics of Research in Psychology. Techniques for the development of research proposals. Statistical techniques for data analysis including non-parametrics, one-way and two-way ANOVA and introduction to correlation and regression.


ST (PSY) 243Introduction to Behavioral Research II LabUNITS: 2 - Offered in Fall and Spring
Prerequisite: PSY or HRD Majors, PSY (ST) 240, Corequisite: PSY (ST) 242
Design and analysis of a major research project.


ST 295Special Topics STUNITS: 1-3


ST 301Statistical Methods IUNITS: 3
Prerequisite: MA 141 and either COS 100 or E 115
Contemporary description and analysis of single samples of data. Graphical data presentation methods for determination of patterns and relationships among variables. Classical and robust alternative methods for single sample data summary procedures.Probability concepts, sampling, and expectations. Confidence interval and hypothesis testing for sample mean and proportion. Computer use emphasized.


ST 302Statistical Methods IIUNITS: 3
Prerequisite: ST 301
Confidence intervals and hypothesis testing with graphics in multiple samples and/or variables cases: tests for means/proportions of two independent groups, analysis of variance for completely randomized design, contingency table analysis, correlation, single and multiple linear regression; design of experiments with randomized blocks, factorial design and analysis of covariance. Computer use emphasized.


ST 305Statistical MethodsUNITS: 4 - Offered in Fall and Spring
Prerequisite: MA 141 and either COS 100 or E 115
Basic concepts of data collection, sampling, and experimental design. Descriptive analysis and graphical displays of data. Probability concepts, and expectations. Normal and binomial distributions. Sampling distributions and the Central Limit Theorem. Confidence intervals and hypothesis testing. Tests for means/proportions of two independent groups. One factor analysis of variance. Understanding relationships among variables; correlation and simple linear regression. Computer use is emphasized.


ST 311Introduction to StatisticsUNITS: 3 - Mathematical Sciences
Examining relationships between two variables using graphical techniques, simple linear regression and correlation methods. Producing data using experiment design and sampling. Elementary probability and the basic notions of statistical inference including confidence interval estimation and tests of hypothesis. One and two sample t-tests, one-way analysis of variance, inference for count data and regression. Credit not allowed if student has prior credit for another ST course or BUS 350


ST 312Introduction to Statistics IIUNITS: 3 - Offered in Fall and Spring, Mathematical Sciences
Prerequisite: ST 311
A further examination of statistics and data analysis. Inference for comparing multiple samples, experimental design, analysis of variance and post-hoc tests. Inference for correlation, simple regression, multiple regression, and curvilinear regression. Analysis of contingency tables and categorical data. No credit for students who have credit for ST 305.


ST (BUS) 350Economics and Business StatisticsUNITS: 3 - Offered in Fall Spring Summer
Prerequisite: MA 114
Introduction to statistics applied to management, accounting, and economic problems. Emphasis on statistical estimation, inference, simple and multiple regression, and analysis of variance. Use of computers to apply statistical methods to problems encountered in management and economics.


ST (EC) 351Data Analysis for EconomistsUNITS: 3 - Offered in Fall Only
Prerequisite: BUS/ST 350
Tools for describing and analyzing data as used in economics. Probability, random variables, sampling, point and interval estimation. Hypothesis testing and regression analysis with emphasis on economic applications.


ST 361Introduction to Statistics for EngineersUNITS: 3 - Offered in Fall Spring Summer, Mathematical Sciences
Prerequisite: College algebra
Statistical techniques useful to engineers and physical scientists. Includes elementary probability, frequency distributions, sampling variation, estimation of means and standard deviations, basic design of experiments, confidence intervals, significance tests, elementary least squares curve fitting. Credit not allowed for both ST 361 and ST 370 or ST 380


ST 370Probability and Statistics for EngineersUNITS: 3 - Offered in Fall and Spring
Prerequisite: MA 241
Calculus-based introduction to probability and statistics with emphasis on Monte Carlo simulation and graphical display of data on computer workstations. Statistical methods include point and interval estimation of population parameters and curve and surface fitting (regression analysis). The principles of experimental design and statistical process control introduced. Credit not allowed for both ST 370 and ST 361 or ST 380


ST 371Introduction to Probability and Distribution TheoryUNITS: 3 - Offered in Fall Spring Summer
Prerequisite: MA 241, Corequisite: MA 242
Basic concepts of probability and distribution theory for students in the physical sciences, computer science and engineering. Provides the background necessary to begin study of statistical estimation, inference, regression analysis, and analysis of variance.


ST 372Introduction to Statistical Inference and RegressionUNITS: 3 - Offered in Fall Spring Summer
Prerequisite: ST 371
Statistical inference and regression analysis including theory and applications. Point and interval estimation of population parameters. Hypothesis testing including use of t, chi-square and F. Simple linear regression and correlation. Introduction to multiple regression and one-way analysis of variance.


ST 380Probability and Statistics for the Physical SciencesUNITS: 3 - Offered in Fall Only
Prerequisite: MA 241
Introduction to probability models and statistics with emphasis on Monte Carlo simulation and graphical display of data on computer laboratory workstations. Statistical methods include point and interval estimation of population parameters and curveand surface fitting (regression analysis). Credit not allowed for both ST 380 and ST 361 or ST 370


ST 401Experiences in Data AnalysisUNITS: 4 - Offered in Summer
Prerequisite: Permission of Instructor and either ST 311 or ST 305
This course will allow students to see many practical aspects of data analysis. Each section of this course will expose students to the process of data analysis in a themed area such as biostatistics or environmental statistics. Students will see problems of data collection and analysis through a combination of classroom demonstrations, hands on computer activities and visits to local industries.


ST (MA) 412Long-Term Actuarial ModelsUNITS: 3 - Offered in Fall Only
Prerequisite: MA 241 or MA 231, Corequisite: MA 421, BUS(ST) 350, ST 301, ST 305, ST 311, ST 361, ST 370, ST 371, ST 380 or equivalent
Long-term probability models for risk management systems. Theory and applications of compound interest, probability distributions of failure time random variables, present value models of future contingent cash flows, applications to insurance, health care, credit risk, environmental risk, consumer behavior and warranties.


ST (MA) 413Short-Term Actuarial ModelsUNITS: 3 - Offered in Summer
Prerequisite: MA 241 or MA 231, and one of MA 421, ST 301, ST 305, ST 370, ST 371, ST 380, ST 421.
Short-term probability models for risk management systems. Frequency distributions, loss distributions, the individual risk model, the collective risk model, stochastic process models of solvency requirements, applications to insurance and businessdecisions.


ST 421Introduction to Mathematical Statistics IUNITS: 3 - Offered in Fall and Summer
Prerequisite: MA 242
First of a two-semester sequence of mathematical statistics, primarily for undergraduate majors and graduate minors in Statistics. Introduction to probability, univariate and multivariate probability distributions and their properties, distributions of functions of random variables, random samples and sampling distributions.


ST 422Introduction to Mathematical Statistics IIUNITS: 3 - Offered in Spring and Summer
Prerequisite: ST 421
Second of a two-semester sequence of mathematical statistics, primarily for undergraduate majors and graduate minors in Statistics. Random samples, point and interval estimators and their properties, methods of moments, maximum likelihood, tests ofhypotheses, elements of nonparametric statistics and elements of general linear model theory.


ST 430Introduction to Regression AnalysisUNITS: 3 - Offered in Fall Only
Prerequisite: (ST 302 or ST 305) and (MA 305 or MA 405)
Regression analysis as a flexible statistical problem solving methodology. Matrix review; variable selection; prediction; multicolinearity; model diagnostics; dummy variables; logistic and non-linear regression. Emphasizes use of computer.


ST 431Introduction to Experimental DesignUNITS: 3 - Offered in Spring Only
Prerequisite: ST 302 or ST 305
Experimental design as a method for organizing analysis procedures. Completely randomized, randomized block, factorial, nested, latin squares, split-plot and incomplete block designs. Response surface and covariance adjustment procedures. Stresses use of computer.


ST 432Introduction to Survey SamplingUNITS: 3 - Offered in Spring Only
Prerequisite: ST 302 or ST 305
Design principles pertaining to planning and execution of a sample survey. Simple random, stratified random, systematic and one- and two-stage cluster sampling designs. Emphasis on statistical considerations in analysis of sample survey data. Class project on design and execution of an actual sample survey.


ST 435Statistical Methods for Quality and Productivity ImprovementUNITS: 3 - Offered in Fall Only
Prerequisite: ST 302 or ST 305
Use of statistics for quality control and productivity improvement. Control chart calculations and graphing, process control and specification; sampling plans; and reliability. Computer use will be stressed for performing calculations and graphing.


ST 445Introduction to Statistical Computing and Data ManagementUNITS: 3 - Offered in Spring and Summer
Corequisite: ST 302 or ST 305
Use of computers to manage, process and analyze data. Concepts of research; data management; JCL and utility programs; use of statistical program package for data analyses and graph production; and writing statistical programs to perform simulationexperiments. Major paper required.


ST 495Special Topics in StatisticsUNITS: 1-6 - Offered in Fall Spring Summer
Offered as needed to present material not normally available in regular departmental course offerings, or for offering new courses on a trial basis.


ST 498Independent Study In StatisticsUNITS: 1-6 - Offered in Fall Spring Summer
Prerequisite: Six hours of ST
Detailed investigation of topics of particular interest to advanced undergraduates under faculty direction.


ST 501Fundamentals of Statistical Inference IUNITS: 3 - Offered in Fall and Summer
Prerequisite: MA 242 or equivalent
First of a two-semester sequence in probability and statistics taught at a calculus-based level. Probability: discrete and continuous distributions, expected values, transformations of random variables, sampling distributions. Credit not given for both ST 521 and ST 501.


ST 502Fundamentals of Statistical Inference IIUNITS: 3 - Offered in Fall and Spring
Prerequisite: ST 501
Second of a two-semester sequence in probability and statistics taught at a calculus-based level. Statistical inference: methods of construction and evaluation of estimators, hypothesis tests, and interval estimators, including maximum likelihood. Credit not given for both ST 522 and ST 502.


ST 503Fundamentals of Linear Models and RegressionUNITS: 3 - Offered in Fall Only
P: ST 501; C: ST 502
Estimation and testing in full and non-full rank linear models. Normal theory distributional properties. Least squares principle and the Gauss-Markov theorem. Estimability, analysis of variance and co variance in a unified manner. Practical model-building in linear regression including residual analysis, regression diagnostics, and variable selection. Emphasis on use of the computer to apply methods with data sets. Credit not given for both ST 552 and ST 503.


ST 505Applied Nonparametric StatisticsUNITS: 3 - Offered in Spring Only
Prerequisite: ST 372 or ST 511
Statistical methods requiring relatively mild assumptions about the form of the population distribution. Hypothesis testing, point and interval estimation and multiple comparison procedures for a variety of statistical problems.


ST 506Sampling Animal PopulationsUNITS: 3 - Offered in Fall Only, Offered Alternate Years
Prerequisite: ST 512
Statistical methods applicable to sampling of wildlife populations, including capture-recapture, removal, change in ratio, quadrant and line transect sampling. Emphasis on model assumptions and study design.


ST 507Statistics For the Behavioral Sciences IUNITS: 3 - Offered in Fall and Spring
A general introduction to the use of descriptive and inferential statistics in behavioral science research. Methods for describing and summarizing data presented, followed by procedures for estimating population parameters and testing hypotheses concerning summarized data.


ST 508Statistics For the Behavioral Sciences IIUNITS: 3 - Offered in Spring Only
Prerequisite: ST 507
Introduction to use of statistical design principles in behavioral science research. Presentation of use of a statistical model to represent structure of data collected from a designed experiment or survey study. Opportunities provided for use of a computer to perform analyses of data, to evaluate proposed statistical model and to assist in post-hoc analysis procedures. Least squares principles used to integrate topics of multiple linear regression analysis, the analysis of variance and analysis of covariance.


ST 511Experimental Statistics For Biological Sciences IUNITS: 3 - Offered in Fall Spring Summer
Prerequisite: ST 311 or Graduate standing
Basic concepts of statistical models and use of samples; variation, statistical measures, distributions, tests of significance, analysis of variance and elementary experimental design, regression and correlation, chi-square.


ST 512Experimental Statistics For Biological Sciences IIUNITS: 3 - Offered in Fall Spring Summer
Prerequisite: ST 511
Covariance, multiple regression, curvilinear regression, concepts of experimental design, factorial experiments, confounded factorials, individual degrees of freedom and split-plot experiments. Computing laboratory addressing computational issues and use of statistical software.


ST 513Statistics for Management IUNITS: 3 - Offered in Fall Only
Prerequisite: Graduate standing
Analysis of data to represent facts, guide decisions and test opinions in managing systems and processes. Graphical and numerical data analysis for descriptive and predictive decisions. Scatter plot smoothing and regression analysis. Basic statistical inference. Integrated use of computer.


ST 514Statistics For Management and Social Sciences IIUNITS: 3 - Offered in Fall Only
Prerequisite: ST 507
Linear regression, multiple regression and concepts of designed experiments in an integrated approach, principles of the design and analysis of sample surveys, use of computer for analysis of data.


ST 515Experimental Statistics for Engineers IUNITS: 3 - Offered in Fall Only
Prerequisite: ST 361 or Graduate standing
General statistical concepts and techniques useful to research workers in engineering, textiles, wood technology, etc. Probability distributions, measurement of precision, simple and multiple regression, tests of significance, analysis of variance,enumeration data and experimental design.


ST 516Experimental Statistics For Engineers IIUNITS: 3 - Offered in Spring Only
Prerequisite: ST 515
General statistical concepts and techniques useful to research workers in engineering, textiles, wood technology, etc. Probability distributions, measurement of precision, simple and multiple regression, tests of significance, analysis of variance, enumeration data and experimental designs.


ST (EMS) 519Teaching and Learning of Statistical ThinkingUNITS: 3 - Offered in Spring Only, Offered Alternate Even Years
Prerequisite: ST 507 or ST 511
This course is designed to bridge theory and practice on how students develop understandings of key concepts in data analysis, statistics, and probability. Discussion of students' understandings, teaching strategies and the use of manipulatives and technology tools. Topics include distribution, measures of center and spread, sampling, sampling distribution, randomness, and law of large numbers. Must complete a first level graduate statistics course ( ST 507, ST 511, or equivalent) before enrolling.


ST 520Statistical Principles of Clinical Trials and EpidemiologyUNITS: 3 - Offered in Fall Only
Prerequisite: ST 511, Corequisite: ST 512
Statistical methods for design and analysis of clinical trials and epidemiological studies. Phase I, II, and III clinical trials. Principle of Intention-to Treat, effects of non-compliance, drop-outs. Interim monitoring of clinical trials and data safety monitoring boards. Introduction to meta-analysis. Epidemiological design and methods.


ST 521Statistical Theory IUNITS: 3 - Offered in Fall Only
Corequisite: MA 425 or MA 511 and MA 405
Probability tools for statistics: description of discrete and absolutely continuous distributions, expected values, moments, moment generating functions, transformation of random variables, marginal and conditional distributions, independence, orderstatistics, multivariate distributions, concept of random sample, derivation of many sampling distributions.


ST 522Statistical Theory IIUNITS: 3 - Offered in Spring Only
Prerequisite: MA 511 or MA 425 and ST 521
General framework for statistical inference. Point estimators: biased and unbiased, minimum variance unbiased, least mean square error, maximum likelihood and least squares, asymptotic properties. Interval estimators and tests of hypotheses: confidence intervals, power functions, Neyman-Pearson lemma, likelihood ratio tests, unbiasedness, efficiency and sufficiency.


ST 524Statistics In Plant ScienceUNITS: 3 - Offered in Fall Only
Prerequisite: ST 512
Principles and techniques of planning, establishing and executing field and greenhouse experiments. Size, shape and orientation of plots; border effects; estimation of size of experiments for specified accuracy; subsampling plots and yields for laboratory analysis; combining data from a series of years and/or locations; rotation experiments; repeated measures data; multiple comparisons in variety trial results; selection of predictors in multiple regression; introduction to interspecies and intraspecies plant competition experiments and models.


ST 535Statistical Process ControlUNITS: 3 - Offered in Fall Only
Prerequisite: ST 515, Students must have access to an MS-DOS PC
Modern methods of statistical process control for graduate students with calculus-level course in engineering statistics. Classical and modern methods of SPC in framework of the Deming quality management philosophy emphasizing continuous process improvement. Orientation toward use of PC-class computers for computations.


ST 536Off-Line Quality ControlUNITS: 3 - Offered in Spring Only
Prerequisite: ST 421 or ST 515
Off-line quality control methods for graduate students with a calculus-level first course in engineering statistics. About one third of lectures presentation of material from area of sampling inspection with emphasis upon using PCs for computations. Remainder of course presentation of material from design of experiments especially important in industrial applications: factorial experiments, orthogonal arrays, Plackett-Burman plans, Box-Behnken designs, response surfaces, design optimality, variability analysis.


ST (MA) 546Probability and Stochastic Processes IUNITS: 3 - Offered in Fall Only
Prerequisite: MA 421 and MA 425 or MA 511
Modern introduction to Probability Theory and Stochastic Processes. The choice of material is motivated by applications to problems such as queueing networks, filtering and financial mathematics. Topics include: review of discrete probability and continuous random variables, random walks, markov chains, martingales, stopping times, erodicity, conditional expectations, continuous-time Markov chains, laws of large numbers, central limit theorem and large deviations.


ST 552Linear Models and Variance ComponentsUNITS: 3 - Offered in Spring Only
Prerequisite: MA 405, ST 521, Corequisite: ST 522
Theory of estimation and testing in full and non-full rank linear models. Normal theory distributional properties. Least squares principle and the Gauss-Markoff theorem. Estimability and properties of best linear unbiased estimators. General linear hypothesis. Application of dummy variable methods to elementary classification models for balanced and unbalanced data. Analysis of covariance. Variance components estimation for balanced data.


ST 555Statistical Programming IUNITS: 3 - Offered in Spring and Summer
An introduction to the data-handling techniques that are required to apply statistical methods including the importing, validating, and exporting of data files; manipulating, subsetting, and grouping data; merging and appending data sets; and basic reports including tables and graphics. Students learn SAS, the industry standard for statistical practice, and the R language commonly used in upper level statistics courses. Regular access to computer for homework and class exercises is required. Credit for both ST 445 and ST 555 is not allowed.


ST 556Statistical Programming IIUNITS: 3 - Offered in Fall Only
P: ST 555 or Base SAS Certification
Statistical procedures for importing/managing complex data structures using SQL, automated analysis using macro programming, basic simulation methods and text parsing/analysis procedures. Students learn SAS, the industry standard for statistical practice. Regular access to a computer for homework and class exercises is required.


ST 557Using Technology to Teach StatisticsUNITS: 3 - Offered in Fall Only
P: ST 508 or ST 512
This course will provide statistics educators with an in-depth introduction to applying technology for teaching college statistics. In this course, students will explore a variety of available statistical packages, demonstration applets, and other technologies for teaching statistics. Students will learn pedagogy t help them structure learning activities around these technologies. Students will also learn to identify key elements in technologies that support pedagogical goals.


ST (ECG) 561Intermediate EconometricsUNITS: 3 - Offered in Spring Only
Prerequisite: ECG 700 and ST 514
Formalization of economic hypotheses into testable relationships and application of appropriate statistical techniques. Major attention to procedures applicable for single equation stochastic models expressing microeconomic and macroeconomic relation-ships. Statistical considerations relevant in working with time series and cross sectional data in economic investigations. Survey of simultaneous equation models and the available estimation techniques.


ST 590Special TopicsUNITS: 1-3 - Offered in Fall Spring Summer


ST 601SeminarUNITS: 1 - Offered in Fall Spring Summer


ST 610Topics in Stat
Special topics in Statistics.


ST 620Special ProblemsUNITS: 1-3 - Offered in Fall Spring Summer
Development of techniques for specialized cases, particularly in connection with thesis and practical consulting problems.


ST 625Advanced Special ProblemsUNITS: 1-3 - Offered in Fall Spring Summer
Prerequisite: ST 512, ST 552
Any new advance in the field of statistics which can be presented in lecture series as unique opportunities arise.


ST 630Independent StudyUNITS: 1-3 - Offered in Fall Spring Summer


ST 635ReadingsUNITS: 1-3 - Offered in Spring Only


ST 641Statistical ConsultingUNITS: 1 - Offered in Fall Spring Summer
Prerequisite: ST 512 and ST 522
Participation in regularly scheduled supervised statistical consulting sessions with faculty member and client. Consultant's report written for each session. Regularly scheduled meetings with course instructor and other student consultants to present and discuss consulting experiences.


ST 685Master's Supervised TeachingUNITS: 1-3 - Offered in Fall Spring Summer
Prerequisite: Master's student
Teaching experience under the mentorship of faculty who assist the student in planning for the teaching assignment, observe and provide feedback to the student during the teaching assignment, and evaluate the student upon completion of the assignment.


ST 688Non-Thesis Masters Continuous Registration - Half Time RegistrationUNITS: 1 - Offered in Fall Spring Summer
Prerequisite: Master's student
For students in non-thesis master's programs who have completed all credit hour requirements for their degree but need to maintain half-time continuous registration to complete incomplete grades, projects, final master's exam, etc.


ST 689Non-Thesis Master Continuous Registration - Full Time RegistrationUNITS: 3 - Offered in Fall Spring Summer
Prerequisite: Master's student
For students in non-thesis master's programs who have completed all credit hour requirements for their degree but need to maintain full-time continuous registration to complete incomplete grades, projects, final master's exam, etc. Students may register for this course a maximum of one semester.


ST 690Master's ExaminationUNITS: 1-6 - Offered in Fall Spring Summer
Prerequisite: Master's student
For students in non thesis master's programs who have completed all other requirements of the degree except preparing for and taking the final master's exam.


ST 693Master's Supervised ResearchUNITS: 1-9 - Offered in Fall Spring Summer
Prerequisite: Master's student
Instruction in research and research under the mentorship of a member of the Graduate Faculty.


ST 695Master's Thesis ResearchUNITS: 1-9 - Offered in Fall Spring Summer
Prerequisite: Master's student
Thesis Research


ST 696Summer Thesis ResearchUNITS: 1 - Offered in Summer
Prerequisite: Master's student
For graduate students whose programs of work specify no formal course work during a summer session and who will be devoting full time to thesis research.


ST 699Master's Thesis PreparationUNITS: 1-9 - Offered in Fall Spring Summer
Prerequisite: Master's student
For students who have completed all credit hour requirements and full-time enrollment for the master's degree and are writing and defending their thesis. Credits Arranged


ST (MA) (OR) 706Nonlinear ProgrammingUNITS: 3 - Offered in Spring Only
Prerequisite: OR(IE,MA) 505 and MA 425
An advanced mathematical treatment of analytical and algorithmic aspects of finite dimensional nonlinear programming. Including an examination of structure and effectiveness of computational methods for unconstrained and constrained minimization. Special attention directed toward current research and recent developments in the field.


ST 708Applied Least SquaresUNITS: 3 - Offered in Fall Only
Prerequisite: ST 512
Least squares estimation and hypothesis testing procedures for linear models. Consideration of regression, analysis of variance and covariance in a unified manner. Emphasis on use of the computer to apply these techniques to experimental (including unequal cell sizes) and survey situations.


ST 711Design Of ExperimentsUNITS: 3 - Offered in Fall Only
Prerequisite: ST 512
Review of completely randomized, randomized complete block and Latin square designs and basic concepts in the techniques of experimental design. Designs and analysis methods in factorial experiments, confounded factorials, response surface methodology, change-over design, split-plot experiments and incomplete block designs. Examples used to illustrate application and analysis of these designs.


ST 715Theory Of Sampling Applied To Survey DesignUNITS: 3 - Offered in Fall Only
Prerequisite: ST 422, ST 512
Principles for interpretation and design of sample surveys. Estimator biases, variances and comparative costs. Simple random sample, cluster sample, ratio estimation, stratification, varying probabilities of selection. Multi-stage, systematic and double sampling. Response errors.


ST (GN) 721Genetic Data AnalysisUNITS: 3 - Offered in Spring Only, Offered Alternate Years
Prerequisite: ST 430 and GN 411
Analysis of discrete data, illustrated with genetic data on morphological characters allozymes, restriction fragment length polymorphisms and DNA sequences. Maximum likelihood estimation, including iterative procedures. Numerical resampling. Development of statistical techniques for characterizing genetic disequilibrium and diversity. Measures of population structure and genetic distance. Construction of phylogenetic trees. Finding alignments and similarities between DNA sequences. Locating genes with markers.


ST 730Applied Time Series AnalysisUNITS: 3 - Offered in Fall Only
Prerequisite: ST 512
An introduction to use of statistical methods for analyzing and forecasting data observed over time. Trigonometric regression, periodogram/spectral analysis. Smoothing. Autoregressive moving average models. Regression with autocorrelated errors. Linear filters and bivariate spectral analysis. Stress on methods and applications; software implementations described and used in assignments.


ST 731Applied Multivariate Statistical AnalysisUNITS: 3 - Offered in Spring Only
Prerequisite: ST 512
An introduction to use of multivariate statistical methods in analysis of data collected in experiments and surveys. Topics covered including multivariate analysis of variance, discriminant analysis, canonical correlation analysis and principal components analysis. Emphasis upon use of a computer to perform multivariate statistical analysis calculations.


ST 732Applied Longitudianal Data AnalysisUNITS: 3 - Offered in Spring Only
Prerequisite: ST 512
Statistics methods for analysis of multivariate data, focusing on data collected in form of repeated measurements. Multivariate normal distribution, Hotelling's T2, multivariate analysis of variance, repeated measures analysis of variance, growth curve models, mixed effects models. Methods for analyzing multivariate data in form of counts, categorical data and binary data, emphasizing recent approaches in statistical literature.


ST 733Applied Spatial StatisticsUNITS: 3 - Offered in Spring Only
Prerequisite: ST 512
Graphical and quantitative description of spatial data. Kriging, block kriging and cokriging. Common variogram models. Analysis of mean-nonstationary data by median polish and universal kriging. Spatial autoregressive models, estimation and testing. Spatial sampling procedures. Use of existing software with emphasis on analysis of real data from the environmental, geological and agricultural sciences.


ST 740Bayesian Inference and AnalysisUNITS: 3 - Offered in Fall Only
Prerequisite: ST 522
Introduction to Bayesian inference; specifying prior distributions; conjugate priors, summarizing posterior information, predictive distributions, hierachical models, asymptotic consistency and asymptotic normality. Markov Chain Monte Carlo (MCMC) methods and the use of exising software(e.g., WinBUGS).


ST 744Categorical Data AnalysisUNITS: 3 - Offered in Spring Only
Prerequisite: ST 512 and ST 522
Statistical models and methods for categorical responses including the analysis of contingency tables, logistic and Poisson regression, and generalized linear models. Survey of asymptotic and exact methods and their implementation using standard statistical software.


ST 745Analysis of Survival DataUNITS: 3 - Offered in Spring Only
Prerequisite: ST 522
Statistical methods for analysis of time-to-event data, with application to situations with data subject to right-censoring and staggered entry, including clinical trials. Survival distribution and hazard rate; Kaplan-Meier estimator for survival distribution and Greenwood's formula; log-rank and weighted long-rank tests; design issues in clinical trials. Regression models, including accelerated failure time and proportional hazards; partial likelihood; diagnostics.


ST (MA) 746Introduction To Stochastic ProcessesUNITS: 3 - Offered in Spring Only
Prerequisite: MA 405 and MA(ST) 546 or ST 521
Markov chains and Markov processes, Poisson process, birth and death processes, queuing theory, renewal theory, stationary processes, Brownian motion.


ST (MA) 747Probability and Stochastic Processes IIUNITS: 3 - Offered in Spring Only
Prerequisite: MA(ST) 546
Fundamental mathematical results of probabilistic measure theory needed for advanced applications in stochastic processes. Probability measures, sigma-algebras, random variables, Lebesgue integration, expectation and conditional expectations w.r.t.sigma algebras, characteristic functions, notions of convergence of sequences of random variables, weak convergence of measures, Gaussian systems, Poisson processes, mixing properties, discrete-time martingales, continuous-time markov chains.


ST (MA) 748Stochastic Differential EquationsUNITS: 3 - Offered in Fall Only
Prerequisite: MA(ST) 747
Theory of stochastic differential equations driven by Brownian motions. Current techniques in filtering and financial mathematics. Construction and properties of Brownian motion, wiener measure, Ito's integrals, martingale representation theorem, stochastic differential equations and diffusion processes, Girsanov's theorem, relation to partial differential equations, the Feynman-Kac formula.


ST (ECG) 750Introduction to Econometric MethodsUNITS: 3 - Offered in Spring Only
Prerequisite: ST 421; Corequisite: ST 422
Introduction to principles of estimation of linear regression models, such as ordinary least squares and generalized least squares. Extensions to time series and panel data. Consideration of endogeneity and instrumental variables estimation. Limited dependent variable and sample selection models. Attention to implementation of econometric methods using a statistical package and microeconomic and macroeconomic data sets.


ST (ECG) 751Econometric MethodsUNITS: 3 - Offered in Fall Only
Prerequisite: ST 421, ST 422
Introduction to important econometric methods of estimation such as Least Squares, instrumentatl Variables, Maximum Likelihood, and Generalized Method of Moments and their application to the estimation of linear models for cross-sectional ecomomic data. Discussion of important concepts in the asymptotic statistical analysis of vector process with application to the inference procedures based on the aforementioned estimation methods.


ST (ECG) 752Time Series EconometricsUNITS: 3 - Offered in Spring Only
Prerequisite: ECG(ST) 751
The characteristics of macroeconomic and financial time series data. Discussion of stationarity and non-stationarity as they relate to economic time series. Linear models for stationary economic time series: autoregressive moving average (ARMA) models; vector autoregressive (VAR) models. Linear models for nonstationary data: deterministic and stochastic trends; cointegration. Methods for capturing volatility of financial time series such as autoregressive conditional heteroscedasticity (ARCH) models. Generalized Method of Moments estimation of nonlinear dynamic models.


ST (ECG) 753MicroeconometricsUNITS: 3 - Offered in Spring Only
Prerequisite: ECG 751
The characteristics of microeconomic data. Limited dependent variable models for cross-sectional microeconomic data: logit/probit models; tobit models; methods for accounting for sample selection; count data models; duration analysis; non-parametricmethods. Panel data models: balanced and unbalanced panels; fixed and random effects; dynamic panel data models; limited dependent variables and panel data analysis.


ST 755Advanced Analysis Of Variance and Variance ComponentsUNITS: 3 - Offered in Spring Only, Offered Alternate Years
Prerequisite: ST 512, ST 552
Expected mean squares, exact and approximate tests of hypotheses for balanced and unbalanced data sets. Fixed, mixed and random models. Randomization theory. Estimation of variance components using regression, MINQUE and general quadratic unbiased estimation theory.


ST (GN) 756Computational Molecular EvolutionUNITS: 3 - Offered in Fall Only, Offered Alternate Years
Prerequisite: GN 411 and ST 511
Phylogenetic analyses of nucleotide and protein sequence data. Sequence alignment, phylogeny reconstruction and relevant computer software. Prediction of protein secondary structure, database searching, bioinformatics and related topics. Project required.


ST (GN) 757Statistics for Molecular Quantitative GeneticsUNITS: 3 - Offered in Fall Only, Offered Alternate Even Years
Prerequisite: ST 512 and GN 703 or ST 721
Genetic mapping data. Linkage map reconstruction, quantitative genetical models. Statistical methods and computer programs for mapping quantitative trait loci and estimating genetic architecture of quantitative traits.


ST 758Computation for Statistical ResearchUNITS: 3 - Offered in Fall Only
Prerequisite: ST 522 and ST 552
Computational tools for research in statistics, including applications of numerical linear algebra, optimization and random number generation, using the statistical language R. A project encompassing a simulation experiment will be required.


ST 762Nonlinear Statistical Models for Univariate and Multivariate ResponseUNITS: 3 - Offered in Fall Only
Prerequisite: ST 512, ST 552
Inference for general nonlinear parametric statistical models for univariate and multivariate continuous and discrete response, including generalized linear models, nonlinear models with nonconstant variance, and generalized estimating equation procedures for multivariate response, including repeated measurement data. Linear and quadratic estimating equations, models for covariance structure, effects of model misspecification and robustness. Survey of major theoretical results and implementation using standard statistical software.


ST (BMA) (MA) 771Biomathematics IUNITS: 3 - Offered in Fall Only
Prerequisite: Advanced calculus, reasonable background in biology
Role of theory construction and model building in development of experimental science. Historical development of mathematical theories and models for growth of one-species populations (logistic and off-shoots), including considerations of age distributions (matrix models, Leslie and Lopez; continuous theory, renewal equation). Some of the more elementary theories on the growth of organisms (von Bertalanffy and others; allometric theories; cultures grown in a chemostat). Mathematical theories oftwo and more species systems (predator-prey, competition, symbosis; leading up to present-day research) and discussion of some similar models for chemical kinetics. Much emphasis on scrutiny of biological concepts as well as of mathematical structureof models in order to uncover both weak and strong points of models discussed. Mathematical treatment of differential equations in models stressing qualitative and graphical aspects, as well as certain aspects of discretization. Difference equation models.


ST (BMA) (MA) 772Biomathematics IIUNITS: 3 - Offered in Spring Only
Prerequisite: BMA 771, elementary probability theory
Continuation of topics of BMA 771. Some more advanced mathematical techniques concerning nonlinear differential equations of types encountered in BMA 771: several concepts of stability, asymptotic directions, Liapunov functions; different time-scales. Comparison of deterministic and stochastic models for several biological problems including birth and death processes. Discussion of various other applications of mathematics to biology, some recent research.


ST (BMA) (MA) (OR) 773Stochastic ModelingUNITS: 3 - Offered in Spring Only, Offered Alternate Years
Prerequisite: BMA 772 or ST (MA) 746
Survey of modeling approaches and analysis methods for data from continuous state random processes. Emphasis on differential and difference equations with noisy input. Doob-Meyer decomposition of process into its signal and noise components. Examples from biological and physical sciences, and engineering. Student project.


ST (MA) 779Advanced ProbabilityUNITS: 3 - Offered in Fall Only
Prerequisite: MA 425 and ST 521.
Sets and classes, sigma-fields and related structures, probability measures and extensions, random variables, expectation and integration, uniform integrability, inequalities, L_p-spaces, product spaces, independence, zero-one laws, convergence notions, characteristic functions, simplest limit theorems, absolute continuity, conditional expectation and conditional probabilities, martingales.


ST 782Time Series Analysis: Time DomainUNITS: 3 - Offered in Spring Only, Offered Alternate Years
Prerequisite: ST 512 and ST 522
Estimation inference for coefficients in autoregressive, moving average and mixed models and large sample. Distribution theory for autocovariances and their use in identification of time series models. Stationarity and seasonality. Extensions of theory and methods to multiple series including vector autoregressions, transfer function models, regression with time series errors, state space modelin


ST 783Time Series Analysis: Frequency DomainUNITS: 3 - Offered in Spring Only, Offered Alternate Years
Prerequisite: ST 512 and ST 522
Theory and methods of time series analysis from frequency point of view. Harmonic analysis, complex demodulation and spectrum estimation. Frequency domain structure of stationary time series and space-time processes. Sampling distributions of commonly used statistics.


ST 784Multivariate AnalysisUNITS: 3 - Offered in Spring Only, Offered Alternate Years
Prerequisite: ST 522
Survey of multivariate statistical theory. Multivariate distributions including the multinormal, Wishart, Hotelling's T, Fisher-Roy-Hsu, Wilks' and multivariate Beta distributions. Applications of maximum likelihood estimation, likelihood ratio testing and the union-intersection principle. Development of the theory of Hotelling's T tests and confidence sets, discriminant analysis, canonical correlation, multivariate analysis of variance and principal components.


ST 790Advanced Special TopicsUNITS: 1-3 - Offered in Fall Spring Summer


ST 793Advanced Statistical InferenceUNITS: 3 - Offered in Spring Only
Prerequisite: ST 522
Statistical inference with emphasis on the use of statistical models, construction and use of likelihoods, general estimating equations, and large sample methods. Includes introduction to Bayesian statistics and the jackknife and bootstrap.


ST 801SeminarUNITS: 1 - Offered in Fall Spring Summer


ST 810Advanced Topics in StatisticsUNITS: 1-3 - Offered in Fall and Spring


ST 820Special ProblemsUNITS: 1-3 - Offered in Fall Spring Summer
Development of techniques for specialized cases, particularly in connection with thesis and practical consulting problems.


ST 825Advanced Special ProblemsUNITS: 1-3 - Offered in Fall Spring Summer
Prerequisite: ST 512, ST 552
Any new advance in the field of statistics which can be presented in lecture series as unique opportunities arise.


ST 830Independent StudyUNITS: 1-3 - Offered in Fall and Spring


ST 835ReadingsUNITS: 1-3 - Offered in Spring Only


ST 841Statistical ConsultingUNITS: 1 - Offered in Fall Spring Summer
Prerequisite: ST 512 and ST 522
Participation in regularly scheduled supervised statistical consulting sessions with faculty member and client. Consultant's report written for each session. Regularly scheduled meetings with course instructor and other student consultants to present and discuss consulting experiences.


ST 885Doctoral Supervised TeachingUNITS: 1-3 - Offered in Fall Spring Summer
Prerequisite: Doctoral student
Teaching experience under the mentorship of faculty who assist the student in planing for the teaching assignment, observe and provide feedback to the student during the teaching assignment, and evaluate the student upon completion of the assignment.


ST 890Doctoral Preliminary ExaminationUNITS: 1-9 - Offered in Fall Spring Summer
Prerequisite: Doctoral student
For students who are preparing for and taking written and/or oral preliminary exams.


ST 893Doctoral Supervised ResearchUNITS: 1-9 - Offered in Fall Spring Summer
Prerequisite: Doctoral student
Instruction in research and research under the mentorship of a member of the Graduate Faculty.


ST 895Doctoral Dissertation ResearchUNITS: 1-9 - Offered in Fall Spring Summer
Prerequisite: Doctoral student
Dissertation Research


ST 896Summer Dissertation ResearchUNITS: 1 - Offered in Summer
Prerequisite: Doctoral student
For graduate students whose programs of work specify no formal course work during a summer session and who will be devoting full time to thesis research.


ST 899Doctoral Dissertation PreparationUNITS: 1-9 - Offered in Fall Spring Summer
Prerequisite: Doctoral student
For students who have completed all credit hour requirements, full-time enrollment, preliminary examination, and residency requirements for the doctoral degree, and are writing and defending their dissertations.