Graduate Course Descriptions

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.

5092. Biostatistics Practicum

1.00 credits | May be repeated for a total of 1 credits.

Prerequisites: None.

Grading Basis: Graded

Participation in two-week Biopharmaceutical Summer Academy. May be repeated for a maximum of three credits with a change of topic.

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5215. Statistical Consulting

Also offered as: STAT 5215

3.00 credits

Prerequisites: BIST/STAT 5315, 5505, and 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.

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5225. Data Management and Programming in R and SAS

Also offered as: STAT 5225

3.00 credits

Prerequisites: BIST/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.

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5505. Applied Statistics I

Also offered as: STAT 5505

3.00 credits

Prerequisites: Open to graduate students in Statistics and Biostatistics; others with permission.

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.

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5515. Design of Experiments

Also offered as: STAT 5515

3.00 credits

Prerequisites: STAT 5005 or graduate student in Biostatistics. Not open for credit to students who have passed STAT 3515Q.

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.

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5585. Mathematical Statistics I

Also offered as: STAT 5585

3.00 credits

Prerequisites: Open to graduate students in Biostatistics, others with permission.

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.

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5605. Applied Statistics II

Also offered as: STAT 5605

3.00 credits

Prerequisites: BIST/STAT 5505.

Grading Basis: Graded

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

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5615. Categorical Data Analysis

3.00 credits

Prerequisites: BIST 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.

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5625. Introduction to Biostatistics

3.00 credits

Prerequisites: Open to graduate students in Biostatistics, others with permission.

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.

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5635. Clinical Trials

3.00 credits

Prerequisites: Open to graduate students in Biostatistics, others with permission.

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.

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5645. Concepts and Analysis of Survival Data

3.00 credits

Prerequisites: Open to graduate students in Biostatistics, others with permission.

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.

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5655. Epidemiology

3.00 credits

Prerequisites: Open to graduate students in Biostatistics, others with permission.

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.

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5685. Mathematical Statistics II

Also offered as: STAT 5685

3.00 credits

Prerequisites: BIST/STAT 5585.

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.

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5705. Statistical Methods in Bioinformatics

3.00 credits

Prerequisites: BIST 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.

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5815. Longitudinal Data Analysis

3.00 credits

Prerequisites: BIST 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.

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6494. Seminar in Biostatistics

3.00 credits | May be repeated for a total of 24 credits.

Prerequisites: Open to graduate students in Biostatistics, others with permission.

Grading Basis: Graded

May be repeated for a total of 24 credits.

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6615. Statistical Learning and Optimization

Also offered as: STAT 6615

3.00 credits

Prerequisites: Instructor consent and intermediate courses in mathematical and applied statistics.

Grading Basis: Graded

Computationally intensive statistical learning methods with optimization techniques: classification, discriminant analysis, (generalized) additive models, boosting, regression trees, regularized regression, principal components, support vector machines, and (deep) neural networks.

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