Course Schedule and Catalog

Long Title: DATA, MODELS, AND REALITY: AN INTRODUCTION TO THE SCIENTIFIC METHOD

Department: Statistics

Grade Mode: Standard Letter

Course Type: Lecture

Distribution Group: Distribution Group III

Credit Hours: 3

Description: The formation of models of reality and the ways models are tested by their analysis in the light of data are considered. We cover a variety of examples from antiquity to the present time.

Long Title: ELEMENTARY APPLIED STATISTICS

Department: Statistics

Grade Mode: Standard Letter

Course Type: Lecture

Distribution Group: Distribution Group III

Credit Hours: 4

Description: Topics include basic probability, descriptive statistics, probability distributions, confidence inervals, significance testing, simple linear regression and correlation, association between categorized variables.

Long Title: MODEL BUILDING

Department: Statistics

Grade Mode: Standard Letter

Course Type: Lecture

Distribution Group: Distribution Group III

Credit Hours: 3

Prerequisite(s): MATH 211

Description: Examples to illustrate mathematical and statistical formulation (modeling) of scienetific problems, their solution and interpretation. Problems from engineering, epidemiology, economics, and other areas are covered. Real-world situations are emphasized.

Long Title: INTRODUCTION TO STATISTICS FOR BIOSCIENCES

Department: Statistics

Grade Mode: Standard Letter

Course Type: Lecture

Distribution Group: Distribution Group III

Credit Hours: 4

Prerequisite(s): MATH 101 AND MATH 102

Description: An introduction to statistics for Biosciences with emphasis on statistical models and data analysis techniques. Computer-assisted data analysis, examples, is explored in laboratory sessions. Topics include descriptive statistics, correlation and regression, categorical data analysis, statistical inference through confidence intervals and significance testing, rates, and proportions, basic epidemiology. Real-world examples are emphasized; for example, genetics, dose-response, biological assays.

Long Title: PROBABILITY AND STATISTICS

Department: Statistics

Grade Mode: Standard Letter

Course Type: Lecture

Distribution Group: Distribution Group III

Credit Hours: 3

Prerequisite(s): MATH 102

Description: Probability and the central concepts and methods of statistics including probability distributions, expectation, estimation, hypothesis testing, sampling distributions, linear models. This seciton presents the general use in multiple disciplines. Cross-list: ECON 382. Recommended prerequisite(s): MATH 212.

Long Title: UNCERTAINTY AND RISK IN URBAN INFRASTRUCTURES

Department: Statistics

Grade Mode: Standard Letter

Course Type: Lecture

Credit Hours: 3

Prerequisite(s): STAT 310

Description: Practical applications adn relevance of infrastructure risk are developed in the context of real engineering problems and phenomena, including unique systems and challenges of the gulf const area. The course starts with a survey of the roles of probability in engineering and focuses on computer-based methods, the Bayesian approach, risk analysis tools, and infrasctructure safety. Cross-list: CEVE 313. Repeatable for Credit.

Long Title: APPLIED PROBABILITY

Department: Statistics

Grade Mode: Standard Letter

Course Type: Lecture

Credit Hours: 3

Prerequisite(s): MATH 212

Description: Elementary probability theory, conditional probability, independence, discrete and continuous random variables, expectation, standard discrete and continuous distributions, transformation techniques, central limit theorems, estimation, and correlation. Selected topics such as the Poisson process, Markov chains, and statistical techniques. Illustrations from engineering are emphasized. Cross-list: ELEC 331.

Long Title: STATISTICAL METHODS-PSYCHOLOGY

Department: Statistics

Grade Mode: Standard Letter

Course Type: Lecture

Credit Hours: 4

Description: See psychology listing for course information.

Long Title: METHODS OF DATA ANALYSIS AND SYSTEM OPTIMIZATION

Department: Statistics

Grade Mode: Standard Letter

Course Type: Lecture

Credit Hours: 4

Prerequisite(s): STAT 280 OR STAT 305 OR STAT 310

Description: The three general topic areas covered in this methodology oriented course are statistical methods including regression, sampling, and experimental design; simulation based methods in statistics, queuing and inventory problems; and an introduction to optimization methods. Excel will serve as the basic computing software.

Long Title: ECONOMETRICS

Department: Statistics

Grade Mode: Standard Letter

Course Type: Lecture

Credit Hours: 3

Description: See economics listing for course information. Cross-list: ECON 400.

Long Title: STATISTICAL COMPUTING AND GRAPHICS

Department: Statistics

Grade Mode: Standard Letter

Course Type: Lecture/Laboratory

Credit Hours: 3

Description: Programming techniques and tools useful and advanced statistical studies. Higher level graphical methods and exploratory data analysis.

Long Title: INTRODUCTION TO REGRESSION AND STATISTICAL COMPUTING

Department: Statistics

Grade Mode: Standard Letter

Course Type: Lecture

Credit Hours: 3

Prerequisite(s): STAT 310 OR STAT 331 or permission of instructor

Description: A survey of regression, linear models, and experimental design. Topics include simple and multiple linear regression, single- and multi-factor studies, analysis of variance, analysis of covariance, model selection, diagnostics. Data analysis using statistical software is emphasized.

Long Title: ADVANCED STATISTICAL METHODS

Department: Statistics

Grade Mode: Standard Letter

Course Type: Lecture

Credit Hours: 3

Prerequisite(s): STAT 310

Description: Advanced topics in statistical applications such as sampling, experimental design and statistical process control.

Long Title: STATISTICAL COMPUTING IN PRACTICE

Department: Statistics

Grade Mode: Standard Letter

Course Type: Laboratory

Credit Hours: 2

Description: Practical aspects of statistical computing, graphics and code development with exposure to multiple software packages, editing environments and hardware platforms.

Long Title: STATISTICAL PROCESS CONTROL AND EXPERIMENTAL DESIGN

Department: Statistics

Grade Mode: Standard Letter

Course Type: Lecture

Credit Hours: 3

Prerequisite(s): STAT 310 OR STAT 331

Description: An historical development of quality control including the approaches of Ford, Pareto, Shewhart, Deming, Box and Tageuchi. Experimental designs include block studies, factorial and fractional factorial designs, crossed and nested factors, balanced designs. Special topics may include sample size determination, response surface methodology, and repeated measures.

Long Title: COMPUTATIONAL FINANCE II: TIME SERIES ANALYSIS

Department: Statistics

Grade Mode: Standard Letter

Course Type: Lecture

Credit Hours: 3

Prerequisite(s): STAT 310

Description: Applied time series modeling and forecasting, with applications to financial markets. STAT 621 is a graduate version of STAT 421 with advanced assignments. Graduate/Undergraduate Equivalency: STAT 621. Recommended prerequisite(s): STAT 410.

Long Title: BAYESIAN DATA ANALYSIS

Department: Statistics

Grade Mode: Standard Letter

Course Type: Lecture

Credit Hours: 3

Prerequisite(s): STAT 410

Description: This course will cover Bayesian methods for analyzing data. The emphasis will be on applied data analysis rather than theoretical development. We will consider a variety of models, including linear regression, hierarchical models, and models for categorical data. Computational methods will be emphasized. Course taught at the University of Texas - Health Science Center. Graduate/Undergraduate Equivalency: STAT 622.

Long Title: PROBABILITY IN BIOINFORMATICS AND GENETICS

Department: Statistics

Grade Mode: Standard Letter

Course Type: Lecture

Credit Hours: 3

Prerequisite(s): STAT 305 OR STAT 310 OR STAT 331 or permission of instructor

Description: Course introduces the student to modern biotechnology and genomic data. Statistical methods to analyze genomic data are covered, including probability models, basic stochastic processes, and statistical modeling. Biological topics include DNA sequence analysis, phylogenetic inference, gene finding, and molecular evolution. UG/GR version: STAT 623. Graduate/Undergraduate Equivalency: STAT 623.

Long Title: OVERVIEW OF MATHEMATICAL STATISTICS

Department: Statistics

Grade Mode: Standard Letter

Course Type: Lecture

Credit Hours: 3

Prerequisite(s): STAT 310 OR STAT 331

Description: Topics include random variables, distributions, transformations, moment generating functions, common families of distributions, independence, sampling distributions, the basics of estimation theory, hypothesis testing and Bayesian inference.

Long Title: PRACTICUM IN STATISTICAL MODELING

Department: Statistics

Grade Mode: Standard Letter

Course Type: Lecture

Credit Hours: 2

Prerequisite(s): LPAP 100

Description: This course introduces current theoretical and applied problems encountered in statistical practice. The content changes each semester in response to contemporary topics. Instructor Permission Required.Graduate/Undergraduate Equivalency: STAT 540.

Long Title: BIOSTATISTICS

Department: Statistics

Grade Mode: Standard Letter

Course Type: Lecture

Credit Hours: 3

Prerequisite(s): STAT 410 or permission of instructor

Description: An overview of statistical methodologies useful in the practice of Biostatistics. Topics include epidemiology, rates, and proportions, categorical data analysis, regression, and logistic regression, retrospective studies, case-control studies, survival analysis. Real biomedical applications serve as context for evaluating assumptions of statistical methods and models. S-Plus (R) serves as computing software. Graduate/Undergraduate Equivalency: STAT 553. Mutually Exclusive: Cannot register for STAT 453 if student has credit for STAT 553.

Long Title: FROM SEQUENCE TO STRUCTURE: AN INTRODUCTION TO COMPUTATIONAL BIOLOGY

Department: Statistics

Grade Mode: Standard Letter

Course Type: Lecture

Credit Hours: 4

Prerequisite(s): COMP 280 AND COMP 212 AND STAT 310 OR STAT 331

Description: Contemporary introduction to problems in computational biology spanning sequence to structure. The course has three modules: the first introduces students to the design and statistical analysis of gene expression studies; the second covers statistical machine learning techniques for understanding experimental data generated in computational biology; and the third introduces problems in the modeling of protein structure using computational methods from robotics. The course is project oriented with an emphasis on computation and problem-solving. Cross-list: BIOE 470, COMP 470.

Long Title: QUANTITATIVE ENVIRONMENTAL DECISION MAKING

Department: Statistics

Grade Mode: Standard Letter

Course Type: Lecture

Credit Hours: 3

Prerequisite(s): STAT 305 AND STAT 385 or permission of instructor

Description: A project oriented computer intensive course focusing on statistical and mathematical solutions and investigations for the purpose of environmental decisions. This course is the undergraduate version of STAT 685 with reduced requirements. Graduate/Undergraduate Equivalency: STAT 685.

Long Title: COMPUTATIONAL FINANCE I: MARKET MODELS

Department: Statistics

Grade Mode: Standard Letter

Course Type: Lecture

Credit Hours: 3

Prerequisite(s): STAT 310 OR STAT 331

Description: This course takes the classical efficient market models and superimposes upon it models for other stochastic phenomena not generally accounted for in efficient market theory, showing how risk is lessened by portfolios and other mechanisms. The course uses computer simulations as an alternative to closed form solutions. UG/GR version: STAT 686. Graduate/Undergraduate Equivalency: STAT 686.

Department: Statistics

Grade Mode: Standard Letter

Course Type: Independent Study

Credit Hours: 1 TO 6

Description:  Repeatable for Credit.

Long Title: INDEPENDENT STUDY

Department: Statistics

Grade Mode: Satisfactory/Unsatisfactory

Course Type: Independent Study

Credit Hours: 0 TO 6

Description:  Repeatable for Credit.

Long Title: INTRODUCTION TO STATISTICS

Department: Statistics

Grade Mode: Standard Letter

Course Type: Lecture

Credit Hours: 3

Description: See political science listing for course information. Cross-list: POLI 495.

Long Title: MATHEMATICAL SCIENCES VIGRE SEMINAR

Department: Statistics

Grade Mode: Standard Letter

Course Type: Seminar

Credit Hours: 1 TO 3

Description: This course prepares a student for research in the mathematical sciences. Each section is dedicated to a different topic. Current topics include bioinformatics, biomathematics, computational finance, simulation driven optimization, and data simulation. Each semester may introduce new topics. Cross-list: CAAM 499, MATH 499, Graduate/Undergraduate Equivalency: STAT 699. Repeatable for Credit.

Long Title: TOPICS IN METHODS AND DATA ANALYSIS

Department: Statistics

Grade Mode: Standard Letter

Course Type: Lecture

Credit Hours: 3

Description: See political science listing for course information. Cross-list: POLI 503.

Long Title: ADVANCED PSYCHOLOGICAL STATISTICS I

Department: Statistics

Grade Mode: Standard Letter

Course Type: Lecture

Credit Hours: 3

Description: See psychology listing for course information. Cross-list: PSYC 502.

Long Title: ADVANCED PSYCHOLOGICAL STATISTICS II

Department: Statistics

Grade Mode: Standard Letter

Course Type: Lecture

Credit Hours: 3

Description: See psychology listing for course information. Cross-list: PSYC 503.

Long Title: MATHEMATICAL STATISTICS I

Department: Statistics

Grade Mode: Standard Letter

Course Type: Lecture

Credit Hours: 3

Prerequisite(s): STAT 581 AND STAT 431 or permission of instructor

Description: The first semester in a two-semester sequence in mathematical statistics: random variables, distributions, small and large sample theorems of hypothesis testing, point estimation, and confidence intervals; topics such as exponential families, univariate and multivariate linear models, and nonparametric inference will also be discussed. Required for graduate students in statistics.

Long Title: ADVANCED STATISTICAL INFERENCE

Department: Statistics

Grade Mode: Standard Letter

Course Type: Lecture

Credit Hours: 3

Prerequisite(s): STAT 582 AND STAT 532

Description: A continuation of STAT 532. Required for Ph.D. students in statistics. Cross-list: CAAM 533.

Long Title: PRACTICUM IN STATISTICAL MODELING

Department: Statistics

Grade Mode: Standard Letter

Course Type: Lecture

Credit Hours: 2

Description: This course introduces current theoretical and applied problems encountered in statistical practice. The content changes each semester in response to contemporary topics. Designed for graduate students in statistics. Graduate/Undergraduate Equivalency: STAT 450. Repeatable for Credit.

Long Title: MULTIVARIATE ANALYSIS

Department: Statistics

Grade Mode: Standard Letter

Course Type: Lecture

Credit Hours: 3

Description: Study of multivariate data analysis and theory. Topics include normal theory, principal components, factor analysis, discrimination, estimation and hypothesis testing, multivariate analysis of variance and regression clustering.

Long Title: SIMULATION

Department: Statistics

Grade Mode: Standard Letter

Course Type: Lecture

Credit Hours: 3

Prerequisite(s): STAT 532

Description: Topics in stochastic simulation including; random number generators; Monte Carlo methods, resampling methods, Markov Chain Monte Carlo, importance sampling and simulation based estimation for stochastic processes.

Long Title: GLM & CATEGORICAL DATA ANALYSIS

Department: Statistics

Grade Mode: Standard Letter

Course Type: Lecture

Credit Hours: 3

Description: Contingency tables, association parameters, chi-squared tests, general theory of generalized linear models, logistics regression, loglinear models, poisson regression.

Long Title: DESIGN AND ANALYSIS OF EXPERIMENTS AND SAMPLING THEORY

Department: Statistics

Grade Mode: Standard Letter

Course Type: Lecture

Credit Hours: 3

Long Title: SURVIVAL ANALYSIS

Department: Statistics

Grade Mode: Standard Letter

Course Type: Lecture

Credit Hours: 3

Description: Lifetime tables, cumulative distribution theory, censored data, Kaplan-Meier survival curves, log-rank tests, Cox proportional hazards models, parametric and non parametric estimation, hypothesis testing.

Long Title: FUNCTIONAL DATA AND WAVELETS

Department: Statistics

Grade Mode: Standard Letter

Course Type: Lecture

Credit Hours: 3

Prerequisite(s): STAT 431 AND STAT 410

Description: Statistical methods for functional data, with emphasis on non-parametric bases representations, such as wavelets. Topics include smoothing of noisy signals, non parametric estimation of densities and regression functions, and representations of stochastic processes. Some emphasis is given to Bayesian inferential procedures. Matlab software is used for class demonstrations. No prior knowledge on wavelets is required.

Long Title: NONPARAMETRIC FUNCTION ESTIMATION

Department: Statistics

Grade Mode: Standard Letter

Course Type: Lecture

Credit Hours: 3

Description: Survey of topics in data analysis including data visualization, multivariate density estimation, and nonparametric regression. Advanced applications will include clustering, discrimination, dimension reduction, and bump-hunting using nonparametric density procedures.

Long Title: ADVANCED TOPICS IN TIME SERIES

Department: Statistics

Grade Mode: Standard Letter

Course Type: Lecture

Credit Hours: 1 TO 3

Description: The course will cover current topics in both modeling and forecasting discrete and continuous time series. A brief coverage will also be given to spatial and spatial-temporal processes. Emphasis will be placed on applications in the area of computational finance.

Long Title: APPLIED STOCHASTIC PROCESSES

Department: Statistics

Grade Mode: Standard Letter

Course Type: Lecture

Credit Hours: 3

Prerequisite(s): STAT 581 AND STAT 582

Description: This course covers the theory of some of the most frequently used stochastic processes in application; discrete and continuous time, Markov chains, Poisson and renewal processes, and Brownian motion.

Long Title: BIOSTATISTICS

Department: Statistics

Grade Mode: Standard Letter

Course Type: Lecture

Credit Hours: 3

Prerequisite(s): STAT 410 or permission of instructor

Description: Same as STAT 453 with advanced problem sets. Graduate/Undergraduate Equivalency: STAT 453. Mutually Exclusive: Cannot register for STAT 553 if student has credit for STAT 453.

Long Title: MATHEMATICAL PROBABILITY I

Department: Statistics

Grade Mode: Standard Letter

Course Type: Lecture

Credit Hours: 3

Description: Measure-theoretic foundations of probability. Open to qualified undergraduates. Cross-list: CAAM 581.

Long Title: MATHEMATICAL PROBABILITY II

Department: Statistics

Grade Mode: Standard Letter

Course Type: Lecture

Credit Hours: 3

Prerequisite(s): STAT 581

Description: Continuation of STAT 581.

Long Title: INTRODUCTION TO RANDOM PROCESSES AND APPLICATIONS

Department: Statistics

Grade Mode: Standard Letter

Course Type: Lecture

Credit Hours: 3

Description: adfasdfasdfasfasdf Cross-list: CAAM 583, ELEC 533.

Long Title: WAVELET AND SPECTRAL ANALYSIS

Department: Statistics

Grade Mode: Standard Letter

Course Type: Lecture

Credit Hours: 3

Description: See ELEC listing for course information. Cross-list: ELEC 532.

Long Title: INDEPENDENT STUDY

Department: Statistics

Grade Mode: Standard Letter

Course Type: Independent Study

Credit Hours: 1 TO 15

Description:  Repeatable for Credit.

Long Title: INDEPENDENT STUDY

Department: Statistics

Grade Mode: Standard Letter

Course Type: Independent Study

Credit Hours: 1 TO 6

Description:  Repeatable for Credit.

Long Title: GRADUATE SEMINAR IN STATISTICS

Department: Statistics

Grade Mode: Standard Letter

Course Type: Seminar

Credit Hours: 1 OR 2

Description: Students participate in the process of researching professional literature (journal articles, book chapters, dissertations), preparing, delivering and critiquing talks. Literature topics change each semester. Repeatable for Credit.

Long Title: ADVANCED ECONOMIC STATISTICS

Department: Statistics

Grade Mode: Standard Letter

Course Type: Lecture

Credit Hours: 5

Description: See ECON listing for course information. Cross-list: ECON 504.

Long Title: ECONOMETRICS I

Department: Statistics

Grade Mode: Standard Letter

Course Type: Lecture

Credit Hours: 5

Long Title: ECONOMETRICS II

Department: Statistics

Grade Mode: Standard Letter

Course Type: Lecture

Credit Hours: 5

Long Title: SPECIAL TOPICS

Department: Statistics

Grade Mode: Standard Letter

Course Type: Lecture

Credit Hours: 3

Description: Seminar on advanced topics in Statistics. Repeatable for Credit.

Long Title: COMPUTATIONAL FINANCE II: TIME SERIES ANALYSIS

Department: Statistics

Grade Mode: Standard Letter

Course Type: Lecture

Credit Hours: 3

Prerequisite(s): STAT 310 OR STAT 331

Description: Applied time series modeling and forecasting, with applications to financial markets with advanced problem sets. UG/GR version: STAT 421. This is a graduate version of STAT 421 with advanced assignments. Graduate/Undergraduate Equivalency: STAT 421. Recommended prerequisite(s): STAT 410

Long Title: BAYESIAN DATA ANALYSIS

Department: Statistics

Grade Mode: Standard Letter

Course Type: Lecture

Credit Hours: 3

Prerequisite(s): STAT 410

Description: This course will cover Bayesian methods for analyzing data. The emphasis will be on applied data analysis rather than theoretical development. We will consider a variety of models, including linear regression, hierarchical models, and models for categorical data. Graduate/Undergraduate Equivalency: STAT 422.

Long Title: PROB BIOFORMATICS & GENETICS

Department: Statistics

Grade Mode: Standard Letter

Course Type: Lecture

Credit Hours: 3

Prerequisite(s): STAT 305 OR STAT 310 OR STAT 331 or permission of instructor

Description: Course introduces the student to modern biotechnology and genomic data. Statistical methods to analyze genomic data are covered, including probability models, basic stochastic processes, and statistical modeling. Biological topics include DNA sequence analysis, phylogenetic inference, gene finding, and molecular evolution. This is a graduate version of STAT 423 with advanced assignments. Graduate/Undergraduate Equivalency: STAT 423.

Long Title: TOPICS IN CLINICAL TRIALS

Department: Statistics

Grade Mode: Standard Letter

Course Type: Lecture

Credit Hours: 3

Description: This course deals with fundamental concepts in the design of clinical studies, ranging from early dose-finding studies (phase I) to screening studies (phase II) to randomized comparative studies (phase III). The goal is to prepare the student to read the clinical trial literature critically and to design clinical studies. Additionally, the faculty will introduce newer designs for clinical studies that incorporate prior knowledge and/or satisfy optimality considerations. Topics include protocol writing; randomization; sample size calculation; study design options; interim monitoring; adaptive designs; multiple end points; and writing up the results of a clinical trial for publication.

Long Title: EXTREME VALUE THEORY

Department: Statistics

Grade Mode: Standard Letter

Course Type: Seminar

Credit Hours: 3

Prerequisite(s): STAT 532

Description: Extreme Value Theory is used in many areas such as financial markets, risk management, environmental studies, as well as network design. In this course we will study the theory and practice of extreme value theory. Recommended prerequisite(s): STAT 533.

Long Title: DATA MINING AND STATISTICAL LEARNING

Department: Statistics

Grade Mode: Standard Letter

Course Type: Lecture

Credit Hours: 3

Description: Survey of ideas, methods, and tools for analyzing large data sets; techniques for searching for unexpected relationships in data. Topics from supervised and unsupervised learning include regression, discriminant analysis, kernels, model selection, bootstrapping, trees, MARS, boosting, classification, clustering, neural networks, SVM, association rules, principal curves, multidimensional scaling, and projection pursuit.

Long Title: ADVANCED SURVIVAL ANALYSIS

Department: Statistics

Grade Mode: Standard Letter

Course Type: Lecture

Credit Hours: 3

Prerequisite(s): STAT 547

Long Title: STOCHASTIC DIFFERENTIAL EQUATIONS

Department: Statistics

Grade Mode: Standard Letter

Course Type: Lecture

Credit Hours: 3

Description: This course will cover both theory and applications of stochastic differential equations. Topics include: the Langevin equation from physics, the Wiener process, white noise, the martingale theory, numerical methods and simulation, the Ito and Stratonovitch theories, applications in finance, signal processing, materials science, biology, and other fields.

Long Title: STATISTICAL GENETICS

Department: Statistics

Grade Mode: Standard Letter

Course Type: Lecture

Credit Hours: 3

Description: This course centers on applications of statistics in genetic problems, especially as they pertain to genotype-phenotype association. Various data structures will be the centerpiece of the course, including genotype, allele-sharing, and gene-expression. Topics include family and population-based study design, linkage, association, differential gene expression. Genetic analysis software will also be discussed and used. *The course will meet at M D Anderson Cancer Prevention Building, CPB4.3650.*

Long Title: ADVANCED METHODS GENOMICS AND PROTEOMICS

Department: Statistics

Grade Mode: Standard Letter

Course Type: Lecture

Credit Hours: 3

Description: We propose to discuss development & application of statistical methods in the analysis of high-throughput boinformatics data that arise from problems in medical research, in particular cancer research, molecular and sturctural biology. We present a broad overview of statistical inference problems related to three main high- throughput platforms: microarray gene expression, serial anaysis gene expression (SAGE), and mass spectrometry proteomic profiles. Our main focus is on the design, statistical inference and data analysis, from a statistician's perspective, of data sets arising from such high throughput experiments.

Department: Statistics

Grade Mode: Standard Letter

Course Type: Lecture

Credit Hours: 3

Description: This course is an introduction to the statistical and bioinformatic analysis of microarray data. The course covers both Affymetrix oligonucleotide arrays and two- color fluorescence cDNA microarrays. The course introduces students to the full range of processing microarray experiments, from experimental design, through image processing, background correction, normalization, and quality control to the downstream statistical analysis of differential expression. The course includes coverage of the key statistical concept of multiple testing. The covers common methods of pattern identification and pattern recognition in the context of microarrays. It also includes the bioinformatic interpretation of the results through tools to interact with public genome databases. All concepts will be illustrated through hands-on interaction with publicly available microarray data sets. Homework assignments will require some knowledge of R, a statistical programming language. The course will include a brief introduction to R. This class meets in the GSBS library (BSRB 53.8351).

Long Title: QUANTITATIVE ENVIRONMENTAL DECISION MAKING

Department: Statistics

Grade Mode: Standard Letter

Course Type: Seminar

Credit Hours: 3

Description: A project oriented computer intensive course focusing on statistical and mathematical solutions and investigations for the purpose of environmental decisions. This course is required for EADM students. Graduate/Undergraduate Equivalency: STAT 485.

Long Title: COMPUTATIONAL FINANCE I: MARKET MODELS

Department: Statistics

Grade Mode: Standard Letter

Course Type: Lecture

Credit Hours: 3

Prerequisite(s): STAT 310 OR STAT 331

Description: This course takes the classical efficient market models and superimposes upon it models for other stochastic phenomena not generally accounted for in efficient market theory, showing how risk is lessened by portfolios and other mechanisms. The course uses computer simulations as an altermative to closed form solutions with advanced problem sets. UG/GR version: STAT 486. Graduate/Undergraduate Equivalency: STAT 486.

Long Title: DECISION THEORY WITH MEDICAL APPLICATION

Department: Statistics

Grade Mode: Standard Letter

Course Type: Lecture

Credit Hours: 3

Prerequisite(s): STAT 422 AND STAT 410 or permission of instructor

Description: Statistical inference, decision theory, and simulation as applied to assist in making individual clinical decisions, policy recommendations, and as a guide to study design and research; topics include statistical decision theory, decision analysis, decision trees, markvo models and simulation, cost-effectiveness analysis, meta-analysis, and sensitivity analysis. Grading will be based on regularly assigned homework exercises and term projects.

Long Title: MATHEMATICAL SCIENCES VIGRE SEMINAR

Department: Statistics

Grade Mode: Standard Letter

Course Type: Seminar

Credit Hours: 1 TO 3

Description: This course prepares a student for research in the mathematical sciences on a specific topic. Each section is dedicated to a different topic. Current topics include bioinformatics, biomathematics, computational finance, simulation driven optimization, and data simulation. The topics change each semester. Cross-list: CAAM 699, MATH 699, Graduate/Undergraduate Equivalency: STAT 499. Repeatable for Credit.

Long Title: THESIS

Department: Statistics

Grade Mode: Standard Letter

Course Type: Research

Credit Hours: 1 TO 15

Description:  Repeatable for Credit.