The following directory lists the graduate courses which the University expects to offer, although the University in no way guarantees that all such courses will be offered in any given academic year, and reserves the right to alter the list if conditions warrant. Click on the links below for a list of courses in that subject area. You may then click “View Classes” to see scheduled classes for individual courses.

### 5005. Introduction to Applied Statistics

3.00 credits

Prerequisites: Not open to students who have passed STAT 2215Q (RG613).

Grading Basis: Graded

One-, two- and k-sample problems, regression, elementary factorial and repeated measures designs, covariance. Use of computer packages, e.g., SAS and MINITAB.

View Classes »### 5099. Investigation of Special Topics

Also offered as: BIST 5099

1.00 - 6.00 credits | May be repeated for a total of 18 credits.

Prerequisites: Open to graduate students in Statistics, others with permission (RG814).

Grading Basis: Graded

### 5105. Quantitative Methods in the Behavioral Sciences

3.00 credits

Prerequisites: Open to graduate students in Statistics, others with permission (RG814).

Grading Basis: Graded

A course designed to acquaint the student with the application of statistical methods in the behavioral sciences. Correlational methods include multiple regression and related multivariate techniques.

View Classes »### 5192. Supervised Research in Statistics

1.00 - 6.00 credits

Prerequisites: Open to graduate students in Statistics, others with permission (RG814).

Grading Basis: Graded

### 5215. Statistical Consulting

Also offered as: BIST 5215

3.00 credits

Prerequisites: At least two of BIST/STAT 5315, 5505, or 5605; or instructor consent.

Grading Basis: Graded

Applied inference for academia, government, and industry: ethical guidelines, observational studies, surveys, clinical trials, designed experiments, data management, aspects of verbal and written communication, case studies.

View Classes »### 5225. Data Management and Programming in R and SAS

Also offered as: BIST 5225

3.00 credits

Prerequisites: Prerequisite: STAT 5505 and 5605; or instructor consent.

Grading Basis: Graded

Creation and management of datasets for statistical analysis: software tools and databases, user-defined functions, importing/exporting/manipulation of data, conditional and iterative processing, generation of reports.

View Classes »### 5315. Analysis of Experiments

3.00 credits

Prerequisites: Prerequisite: STAT 5005. Not open to students who have passed STAT 3115Q (RG614).

Grading Basis: Graded

Straight-line regression, multiple regression, regression diagnostics, transformations, dummy variables, one-way and two-way analysis of variance, analysis of covariance, stepwise regression.

View Classes »### 5361. Statistical Computing

Also offered as: BIST 5361

3.00 credits

Prerequisites: Open to graduate students in Statistics, others with permission (RG814).

Grading Basis: Graded

Use of computing for statistical problems; obtaining features of distributions, fitting models and implementing inference. Basic numerical methods, nonlinear statistical methods, numerical integration, modern simulation methods.

View Classes »### 5415. Advanced Statistical Methods

3.00 credits

Prerequisites: Open to graduate students in Statistics, others with permission (RG814).

Grading Basis: Graded

Discrete and continuous random variables, exponential family, joint and conditional distributions, order statistics, statistical inference: point estimation, confidence interval estimation, and hypothesis testing.

View Classes »### 5505. Applied Statistics I

Also offered as: BIST 5505

3.00 credits

Prerequisites: Open to graduate students in Statistics, others with permission (RG814).

Grading Basis: Graded

Exploratory data analysis: stem-and leaf plots, Box-plots, symmetry plots, quantile plots, transformations, discrete and continuous distributions, goodness of fit tests, parametric and non-parametric inference for one sample and two sample problems, robust estimation, Monte Carlo inference, bootstrapping.

View Classes »### 5515. Design of Experiments

Also offered as: BIST 5515

3.00 credits

Prerequisites: Prerequisite: STAT 5005. Not open to students who have passed STAT 3515Q (RG615).

Grading Basis: Graded

One way analysis of variance, multiple comparison of means, randomized block designs, Latin and Graeco-Latin square designs, factorial designs, two-level factorial and fractional factorial designs, nested and hierarchical designs, split-plot designs.

View Classes »### 5525. Sampling Theory

Also offered as: BIST 5525

3.00 credits

Prerequisites: Open to graduate students in Statistics, others with permission (RG814).

Grading Basis: Graded

Sampling and nonsampling error, bias, sampling design, simple random sampling, sampling with unequal probabilities, stratified sampling, optimum allocation, proportional allocation, ratio estimators, regression estimators, super population approaches, inference in finite populations.

View Classes »### 5535. Nonparametric Methods

Also offered as: BIST 5535

3.00 credits

Prerequisites: Not open to students who have passed STAT 4875.

Grading Basis: Graded

Theory and applications of statistical methods for analyzing ordinal, non-normal data: one and multiple sample hypothesis testing, empirical distribution functions and applications, order statistics, rank tests, efficiency, linear and nonlinear regression, classification.

View Classes »### 5585. Mathematical Statistics I

Also offered as: BIST 5585

3.00 credits

Prerequisites: Open to graduate students in Statistics, others with permission (RG814).

Grading Basis: Graded

Introduction to probability theory, transformations and expectations, moment generating function, discrete and continuous distributions, joint and marginal distributions of random vectors, conditional distributions and independence, sums of random variables, order statistics, convergence of a sequence of random variables, the central limit theorem.

View Classes »### 5605. Applied Statistics II

Also offered as: BIST 5605

3.00 credits

Prerequisites: Prerequisite: STAT 5505 (RG815).

Grading Basis: Graded

Analysis of variance, regression and correlation, analysis of covariance, general liner models, robust regression procedures, and regression diagnostics.

View Classes »### 5615. Categorical Data Analysis

Also offered as: BIST 5615

3.00 credits

Prerequisites: Prerequisite: STAT 5505 and 5605; or instructor consent.

Grading Basis: Graded

Statistical analysis of data on a nominal scale: discrete distributions, contingency tables, odds ratios, interval estimates, goodness of fit tests, logistic/probit/complementary log-log regression, Poisson-related regression.

View Classes »### 5625. Introduction to Biostatistics

Also offered as: BIST 5625

3.00 credits

Prerequisites: Open to graduate students in Statistics, others with permission (RG814).

Grading Basis: Graded

Rates and proportions, sensitivity, specificity, two-way tables, odds ratios, relative risk, ordered and non-ordered classifications, rends, case-control studies, elements of regression including logistic and Poisson, additivity and interaction, combination of studies and meta-analysis.

View Classes »### 5635. Clinical Trials

Also offered as: BIST 5635

3.00 credits

Prerequisites: Open to graduate students in Statistics, others with permission (RG814).

Grading Basis: Graded

Basic concepts of clinical trial analysis; controls, randomization, blinding, surrogate endpoints, sample size calculations, sequential monitoring, side-effect evaluation and intention-to-treat analyses. Also, experimental designs including dose response study, multicenter trials, clinical trials for drug development, stratification, and cross-over trials.

View Classes »### 5645. Concepts and Analysis of Survival Data

Also offered as: BIST 5645

3.00 credits

Prerequisites: Open to graduate students in Statistics, others with permission (RG814).

Grading Basis: Graded

Survival models, censoring and truncation, nonparametric estimation of survival functions, comparison of treatment groups, mathematical and graphical methods for assessing goodness of fit, parametric and nonparametric regression models.

View Classes »### 5655. Epidemiology

Also offered as: BIST 5655

3.00 credits

Prerequisites: Open to graduate students in Statistics, others with permission (RG814).

Grading Basis: Graded

The statistical study of health and illness in human and veterinary populations: epidemiological study designs, measures of disease frequency/effect/potential impact, selection and information biases, confounding, stratified analysis.

View Classes »### 5665. Applied Multivariate Analysis

Also offered as: BIST 5665

3.00 credits

Prerequisites: Open to graduate students in Statistics, others with permission (RG814).

Grading Basis: Graded

Multivariate normal distributions, inference about a mean vector, comparison of several multivariate means, principal components, factor analysis, canonical correlation analysis, discrimination and classification, cluster analysis.

View Classes »### 5675. Bayesian Data Analysis

Also offered as: BIST 5675

3.00 credits

Prerequisites: Prerequisite: STAT 5585 and 5685; or instructor consent.

Grading Basis: Graded

Theory of statistical inference based on Bayes' Theorem: basic probability theory, linear/nonlinear, graphical, and hierarchical models, decision theory, Bayes estimation and hypothesis testing, prior elicitation, Gibbs sampling, the Metropolis-Hastings algorithm, Monte Carlo integration.

View Classes »### 5685. Mathematical Statistics II

Also offered as: BIST 5685

3.00 credits

Prerequisites: Prerequisite: STAT 5585 (RG816).

Grading Basis: Graded

The sufficiency principle, the likelihood principle, the invariance principle, point estimation, methods of evaluating point estimators, hypotheses testing, methods of evaluating tests, interval estimation, methods of evaluating interval estimators.

View Classes »### 5705. Statistical Methods in Bioinformatics

Also offered as: BIST 5705

3.00 credits

Prerequisites: Prerequisite: STAT 5505 and 5585; or instructor consent.

Grading Basis: Graded

Statistical methods and software tools for the analysis of biological data: sequencing methods; gene alignment methods; expression analysis; evolutionary models; analysis of proteomics, metabolomics, and methylation data; pathway analysis: gene network analysis.

View Classes »### 5725. Linear Statistical Models

Also offered as: BIST 5725

3.00 credits

Prerequisites: Open to graduate students in Statistics, others with permission (RG814).

Grading Basis: Graded

Linear and matrix algebra concepts, generalized inverses of matrices, multivariate normal distribution, distributions of quadratic forms in normal random vectors, least squares estimation for full rank and less than full rank linear models, estimation under linear restrictions, testing linear hypotheses.

View Classes »### 5815. Longitudinal Data Analysis

Also offered as: BIST 5815

3.00 credits

Prerequisites: Prerequisite: STAT 5505 and 5605; or instructor consent.

Grading Basis: Graded

Statistical theory and methodology for data collected over time in a clustered manner: design of experiments, exploratory data analysis, linear models for continuous data, general linear models for discrete data, marginal and mixed models, treatment of missing data.

View Classes »### 5825. Applied Time Series

Also offered as: BIST 5825

3.00 credits

Prerequisites: Open to graduate students in Statistics, others with permission (RG814).

Grading Basis: Graded

Introduction to prediction using time-series regression methods with non-seasonal and seasonal data. Smoothing methods for forecasting. Modeling and forecasting using univariate autoregressive moving average models.

View Classes »### 6315. Statistical Inference I

3.00 credits

Prerequisites: Open to graduate students in Statistics, others with permission (RG814).

Grading Basis: Graded

Exponential families, sufficient statistics, loss function, decision rules, convexity, prior information, unbiasedness, Bayesian analysis, minimaxity, admissibility, simultaneous and shrinkage estimation, invariance, equivariant estimation.

View Classes »### 6325. Advanced Probability

3.00 credits

Prerequisites: Open to graduate students in Statistics, others with permission (RG814).

Grading Basis: Graded

Fundamentals of measure and integration theory: fields, o-fields, and measures; extension of measures; Lebesgue-Stieltjes measures and distribution functions; measurable functions and integration theorems; the Radon-Nikodym Theorem, product measures, and Fubini's Theorem. Introduction to measure-theoretic probability: probability spaces and random variables; expectation and moments; independence, conditioning, the Borel-Cantelli Lemmas, and other topics as time allows.

View Classes »### 6494. Seminar in Applied Statistics

Also offered as: BIST 6494

1.00 - 6.00 credits | May be repeated for a total of 24 credits.

Prerequisites: Open to graduate students in Statistics, others with permission (RG814).

Grading Basis: Graded

### 6515. Statistical Inference II

3.00 credits

Prerequisites: Prerequisite: STAT 6315; Open to graduate students in Statisitcs, others with permission. (RG527).

Grading Basis: Graded

Statistics and subfields, conditional expectations and probability distributions, uniformly most powerful tests, uniformly most powerful unbiased tests, confidence sets, conditional inference, robustness, change point problems, order restricted inference, asymptotics of likelihood ratio tests.

View Classes »### 6694. Seminar in Multivariate Statistics

1.00 - 6.00 credits | May be repeated for a total of 12 credits.

Prerequisites: Open to graduate students in Statistics, others with permission (RG814).

Grading Basis: Graded

### 6894. Seminar in the Theory of Probability and Stochastic Processes

1.00 - 6.00 credits | May be repeated for a total of 12 credits.

Prerequisites: Open to graduate students in Statistics, others with permission (RG814).

Grading Basis: Graded