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 Graduate Course Descriptions
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More information can be found by looking at the syllabi for past classes. Updated 11/3/03.

6448 Advanced Probability and Inference II (3)
The course covers unbiased and locally most powerful tests (including the multiparameter case); envelope power function; best average power test; Bayes and empirical Bayes procedures; likelihood, quasi likelihood, and profile likelihood; order statistics and empirical distributions; general central limit theorems; variance stabilizing transformations; U-statistics; least squares, weighted least squares, and generalized least squares estimation; generalized estimating equations; asymptotic theory for BAN estimators; asymptotic theory for likelihood ratio, Wald, and score tests; log-linear models; asymptotics for linear inference; as well as robust statistical inference
Prerequisite: STA5326 and STA5327

STA 5106 Computational Methods in Statistics I (3)
Matlab and a programming language (C/Fortran) will be used. Floating point arithmetic, numeric matrix analysis, multiple regression analysis, nonlinear optimization, root finding, numerical integration, Monte Carlo sampling.
Prerequisite: At least one previous coarse in statistics above STA 1013; some previous programming experience; or permission of the instructor.

STA 5107 Computational Methods in Statistics II (3)
Matlab and a programming language (C/Fortran) will be used. A continuation of STA 5106 in computational techniques for linear and nonlinear statistics. Statistical image understanding, elements of pattern theory, simulated annealing, Metropolis-Hastings algorithm, Gibbs sampling.
Prerequisite: STA 5106 or permission of the instructor.

STA 5126 Introduction to Applied Statistics (3)
Data collection, sample variation, basic probability, confidence intervals, hypothesis testing, analysis of variance, contingency tables, correlation, regression, nonparametric statistics.
Prerequisite: MAC 1105
Special Note: Graduate credit for non-statistics majors only.

STA 5166 Statistics in Applications I (3)
Comparison of two treatments, random sampling, and randomization and blocking with two comparisons, statistical inference for means, variances, proportions and frequencies, and analysis of variance.
Prerequisite: MAC 2313

STA 5167 Statistics in Applications II (3)
Special designs in analysis of variance, linear and nonlinear regression, least squares and weighted least squares, case analysis, model building, non least squares estimation.
Prerequisite: STA 5166

STA 5168 Statistics in Applications III (3)
Response surface methods, repeated measures and split-plot designs, basic log-linear and logit models for two-way and multiway tables, and multinomial response models.
Prerequisite: STA 5167

STA 5169 Advanced Applied Statistics (3)
Contemporary methods in applied statistics; resampling methods including bootstrapping; nonparametric regression.
Prerequisite: STA 5167, 5327

STA 5172 Statistics in Epidemiology (3)
This course introduces the statistical methods developed for and used in epidemiology. Topics to be covered include: Statistical design issues in epidemiological studies, measures of disease occurrence, measures of association, and adjusting for confounding without and with multivariate models.

STA 5176 Statistical Modeling with Applications to Biology (3)
Maximum likelihood principle, missing data and EM algorithm; assessment tools such as bootstrap and cross-validation; Markov chain and hidden Markov models; classification and regression tress (CART); Bayesian models and Markov Chain Monte Carlo algorithms..
Prerequisite: STA 4442 or 5440

STA 5179 Applied Survival Analysis (3)
This course will offer a focused introduction to methods for describing, analyzing, and modeling survival data in medical studies.
Prerequisite: STA 2171 or permission of the instructor.

STA 5206 Analysis of Variance and Design of Experiments (3)
One and two-way classifications, nesting, blocking, multiple comparisons, incomplete designs, variance components, factorial designs, confounding.
Prerequisite: One of STA 2122, 4322, 5126 or 5354.
Special Note: Graduate credit for non-statistics majors only.

STA 5207 Applied Regression Methods (3)
General linear hypothesis, analysis of covariance, multiple correlation and regression, response surface methods.
Prerequisite: One of STA 2122, 4322, 5126, or 5354.
Special Note: Graduate credit for non-statistics majors only.

STA 5208 Linear Statistical Models (3)

Prerequisite: STA 5327

STA 5225 Sample Surveys (3)
Simple stratified, systematic, and cluster random sampling. Ratio and regression estimation. Multistage sampling.
Prerequisite: A course in statistics above STA 1013 or consent of instructor.

STA 5238 Applied Logistic Regression (3)
his course will offer a focused introduction to logistic regression for modeling a dichotomous response as a function of patient characteristics. Topics to be covered include methods of fitting the model, model interpretation, some topics in model building, assessing model fit, applications in cohort, case-control, and complex surveys and use in matched case-control studies.
Prerequisite: STA 2171 or permission of the instructor.

STA 5244 Clinical Trials (3)
This course will introduce practical as well as statistical issues in the design and analysis of clinical trials. Topics to be covered include basic study design, methods of randomization and blinding, samples size, recruitment and compliance, data collection and quality control, and issues in the analysis and reporting the results of clinical trials.
Prerequisite: 2171 or permission of instructor.

STA 5325 Mathematical Statistics (3)
Sufficiency, point estimation, confidence intervals, hypothesis testing, regression, linear models, Bayesian models.
Prerequisite: STA 4442 or 5440 and either MAC 2313 or STA 5326.

STA 5326 Distribution Theory and Inference (3)
Introduction to Probability, random variables, distributions, limit laws, conditional distributions, and expectations.
Prerequisite: MAC 2313; at least one previous course in statistics or probability.

STA 5327 Statistical Inference (3)
Statistical Inference viewed at a measure-theoretic level.
Prerequisite: STA 5326, 5446

STA 5334 Limit Theory of Statistics (3)
Convergence of distribution and random variables, laws of large numbers, central limit theorems, asymptotic distributions, asymptotic efficiency, rates of convergence, the weak invariance principle.
Prerequisite: STA 5327

STA 5440 Introductory Probability I (3)
Random variables, probability of random variables, generating functions, central limit theorem, laws of large numbers.
Prerequisite: MAC 2311

STA 5446 Probability and Measure (3)
Classes of sets, probability measures, construction of probability measures, random variables, expectation and integration, independence and product measures.
Prerequisite: MAA 4227, 5307, or the equivalent.

STA 5447 Probability Theory (3)

Prerequisite: STA 5326, STA 5446

STA 5507 Applied Nonparametric Statistics (3)
Applications of nonparametric tests, estimates, confidence intervals, multiple comparison procedures, multivariate nonparametric methods, and nonparametric methods for censored data.
Prerequisite: A course in statistics above STA 1013 or consent of instructor.

STA 5526 Nonparametric and Rank Order Statistics (3)
Distribution-free test, distribution-free confidence intervals and bands, nonparametric estimation, efficiency, robustness, resampling methods.
Prerequisite: STA 5327

STA 5619 Operations Research: Linear and Dynamic Programming (3)
Techniques of optimization deterministic and stochastic processes, time dependent or time independent, the simplex method, duality, application to game theory, Bellman's recursion equations, applications to problems in science, economics, industry, and engineering.
Prerequisite: MAC 2312

STA 5666 Statistics for Quality and Productivity (3)
Statistics for quality control and productivity; graphical methods; control charts; acceptance sampling; design and experiment for product and process improvement.
Prerequisite: STA 5167 or consent of the instructor, and either STA 4322 or 5126.

STA 5676 Reliability Theory and Life Testing (4)

Prerequisite: A basic course in probability and statistics.

STA 5707 Applied Multivariate Analysis (3)
Inference about mean vectors and covariance matrices, canonical correlation, principal components, discriminant analysis, cluster analysis, computer techniques.
Prerequisite: One of STA 5167, 5207, or 5327.

STA 5746 Multivariate Analysis (3)

Prerequisite: STA 5327

STA 5807r Topics in Stochastic Processes (3)

Prerequisite: STA 5326
Special Note: May be repeated to a maximum of twelve (12) semester hours.

STA 5856 Time Series and Forecasting Methods (3)
Autoregressive, moving average and mixed models, autocovariance and autocorrelation functions, model identification, forecasting techniques, seasonal model identification estimation and forecasting, intervention and transfer function model identification, estimation and forecasting.
Prerequisite: STA 5126, QMB 3200, or equivalent.

STA 5906r Directed Individual Study (1-12)

Special Note: (S/U grade only). May be repeated.

STA 5910r Supervised Research (1-6)

Special Note: (S/U grade only.) May be repeated to a maximum of twelve (12) semester hours. A maximum of three (3) hours may apply to the master's degree

STA 5920r Statistics Colloquium (1)

Special Note: (S/U grade only.) May be repeated to a maximum of twelve (12) semester hours.

STA 5934r Selected Topics in Statistics, Probability, or Operations Research (2-3)

Special Note: May be repeated to a maximum of twelve (12 )semester hours.

STA 5936 Graduate Orientation Seminar (1)

Special Note: (S/U grade only.)

STA 5938 Topics in Medical Consulting (3)
Experience in consulting by actual consultation with researchers doing epidemiological and medical research. Two to four consulting problems will be identified. Investigators will present the problem to the class and will be available to answer questions after the initial meeting. Statistical topics covered will be those identified by the class as required to solve the problems presented.
Prerequisite: STA 2171 or permission of instructor.

STA 5939 Introduction to Statistical Consulting (1-3)
Formulation of statistical problems from client information; the analysis of complex data sets by computer; practical consulting experience.
Prerequisite: STA 5167; 5354 or 5327.
Special Note: (S/U grade only.)

STA 5940r Supervised Consulting (1-3)

Special Note: (S/U grade only.) May be repeated to a maximum of twelve (12) semester hours. A maximum of three (3) hours may apply to the master's degree.

STA 5971r Thesis (3-6)

Special Note: (S/U grade only.) Six (6) semester hours credit required.

STA 6174 Advanced Methods in Epidemiology (3)
This course will offer advanced methods for describing, analyzing, and modeling data from observational studies. Topics will vary with each offering. Initial topics include bootstrap methodology, randomization tests, and meta-analytic methods. All of the methods presented will be illustrated with case studies and problem sets involving a database of 27 observational studies of cardiovascular disease.
Prerequisite: STA 5167 and 5325 or permission of instructor.

STA 6246r Advanced Topics in Applied Statistics ()


STA 6346 Advanced Probability and Inference I (3)
The course covers the basics of the probability theory, random elements, and stochastic processes; characteristic functions and probability inequalities; central limit theorems; elements of Markov dependence and martingale theory; common scholastic processes arising in biostatistics; advanced treatment of sufficient statistics, exponential families, estimation, and testing; as well as elements of asymptotic theory of statistical inference.
Prerequisite: STA 5326 and STA 5327

STA 6448 Advanced Probability and Inference II (3)
The course covers unbiased and locally most powerful tests (including the multiparameter case); envelope power function; best average power test; Bayes and empirical Bayes procedures; likelihood, quasi likelihood, and profile likelihood; order statistics and empirical distributions; general central limit theorems; variance stabilizing transformations; U-statistics; least squares, weighted least squares, and generalized least squares estimation; generalized estimating equations; asymptotic theory for BAN estimators; asymptotic theory for likelihood ratio, Wald, and score tests; log-linear models; asymptotics for linear inference; as well as robust statistical inference.
Prerequisite: STA5326 and STA5327

STA 6468 Advanced Topics in Probability and Statistics (2-3)

Special Note: May be repeated to a maximum of twelve (12) semester hours.

STA 6555 Nonparametric Curve Estimation (3)
Estimation of regression and density functions and their derivatives where no parametric model is assumed. Kernel, local polynomial, spline, and wavelet methods. Emphasis on analysis and applications of the smoothing techniques, and data-based smoothing parameter selectors.
Prerequisite: STA 55327 or consent of instructor.

STA 6709 Spatial Statistics (3)
Familiarity with S-Plus or SAS software. Methods for the analysis of spatial data, including geostatistical data, lattice data, and point patterns. Theory and applications of basic principles and techniques.
Prerequisite: STA 5208, 5327.

STA 6906r Directed Individual Study (1-12)

Special Note: (S/U grade only.) May be repeated.

STA 8961 Statistics Proficiency Examination ()


STA 8964 Preliminary Doctoral Examination ()


STA 8966 Master's Comprehensive Examination ()


STA 8976 Master's Thesis Defense ()


STA 8985 Defense of Dissertation ()



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