### 5005. Introduction to Applied Statistics

Three credits. Not open for credit to students who have passed STAT 2215Q.

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

### 5099. Investigation of Special Topics

(Also offered as BIST 5099.) Variable (1-6) credits. Prerequisite: Open only to Statistics graduate students; instructor consent required. May be repeated for credit.

### 5105. Quantitative Methods in the Behavioral Sciences

Three credits. Prerequisite: Open only to Statistics graduate students, others with consent.

Acquaints the student with the application of statistical methods in the behavioral sciences. Correlational methods include multiple regression and related multivariate techniques.

### 5192. Supervised Research in Statistics

Variable (1-6) credits. Prerequisite: Open only to Statistics graduate students, others with consent.

### 5215. Statistical Consulting

(Also offered as BIST 5215.) Three credits. Prerequisite: STAT 5315, 5505, 5605, and 5725; or instructor consent.

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.

### 5225. Data Management and Programming in R and SAS

(Also offered as BIST 5225.) Three credits. Prerequisite: STAT 5505 and 5605; or instructor consent.

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.

### 5315. Analysis of Experiments

Three credits. Prerequisite: STAT 5005. Not open for credit to students who have passed STAT 3115Q.

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

### 5361. Statistical Computing

(Also offered as BIST 5361.) Three credits. Prerequisite: Open only to Statistics graduate students, others with consent.

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.

### 5415. Advanced Statistical Methods

Three credits. Prerequisite: Open only to Statistics graduate students; instructor consent required.

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

### 5505. Applied Statistics I

(Also offered as BIST 5505.) Three credits. Prerequisite: Open only to Statistics graduate students, others with consent.

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.

### 5515. Design of Experiments

(Also offered as BIST 5515.) Three credits. Prerequisite: STAT 5005 or enrollment in Statistics M.A. or Ph.D. program. Not open for credit to students who have passed STAT 3515Q.

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.

### 5525. Sampling Theory

(Also offered as BIST 5525.) Three credits. Prerequisite: Open only to Statistics graduate students, others with consent.

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.

### 5535. Nonparametric Methods

(Also offered as BIST 5535.) Three credits. Not open to students who have passed STAT 4875.

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.

### 5585. Mathematical Statistics I

(Also offered as BIST 5585.) Three credits. Prerequisite: Open only to Statistics graduate students, others with consent.

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.

### 5605. Applied Statistics II

(Also offered as BIST 5606.) Three credits. Prerequisite: STAT 5505.

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

### 5615. Categorical Data Analysis

(Also offered as BIST 5615.) Three credits. Prerequisite: STAT 5505 and 5605; or instructor consent.

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.

### 5625. Introduction to Biostatistics

(Also offered as BIST 5625.) Three credits. Prerequisite: Open only to Statistics graduate students; instructor consent required.

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.

### 5635. Clinical Trials

(Also offered as BIST 5635.) Three credits. Prerequisite: Open only to Statistics graduate students; instructor consent required.

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.

### 5645. Concepts and Analysis of Survival Data

(Also offered as BIST 5645.) Three credits. Prerequisite: Open only to Statistics graduate students; instructor consent required.

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.

### 5655. Epidemiology

(Also offered as BIST 5655.) Three credits. Prerequisite: Open to graduate students in the Department of Statistics; others with consent.

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.

### 5665. Applied Multivariate Analysis

(Also offered as BIST 5665.) Three credits. Prerequisite: Open only to Statistics graduate students, others with consent.

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.

### 5675. Bayesian Data Analysis

(Also offered as BIST 5675.) Three credits. Prerequisite: STAT 5585 and 5685; or instructor consent.

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.

### 5685. Mathematical Statistics II

(Also offered as BIST 5685.) Three credits. Prerequisite: STAT 5585.

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.

### 5705. Statistical Methods in Bioinformatics

(Also offered as BIST 5705.) Three credits. Prerequisite: STAT 5505 and 5585; or instructor consent.

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.

### 5725. Linear Statistical Models

(Also offered as BIST 5725.) Three credits. Prerequisite: Open only to Statistics graduate students, others with consent.

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.

### 5815. Longitudinal Data Analysis

(Also offered as BIST 5815.) Three credits. Prerequisite: STAT 5505 and 5605; or instructor consent.

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.

### 5825. Applied Time Series

(Also offered as BIST 5825.) Three credits. Prerequisite: Open only to Statistics graduate students, others with consent.

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.

### 6315. Statistical Inference I

Three credits. Prerequisite: Open only to Statistics graduate students, others with consent.

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

### 6325. Advanced Probability

Three credits. Prerequisite: Open only to Statistics graduate students, others with consent.

Fundamentals of measure and integration theory: ields, 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.

### 6494. Seminar in Applied Statistics

(Also offered as BIST 6494.) Variable (1-6) credits. Prerequisite: Open only to Statistics graduate students, others with consent. May be repeated for credit.

### 6515. Statistical Inference II

Three credits. Prerequisite: STAT 6315; open only to Statistics graduate students, others with consent.

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.

### 6694. Seminar in Multivariate Statistics

Variable (1-6) credits. Prerequisite: Open only to Statistics graduate students, others with consent. May be repeated for a total of 12 credits.

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

Variable (1-6) credits. Prerequisite: Open only to Statistics graduate students, others with consent. May be repeated for a total of 12 credits.