UM SPH Department of Biostatistics Courses

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BIOSTAT449 Topics In Biostatistics

Winter term(s)
3 Credit Hour(s)
Instructor(s): Staff
Prerequisites: Statistics 401 or permission of instructor
Description: This course will make use of case studies to discuss problems and applications of biostatistics. Topics will include cohort and case control studies, survival analysis with applications in clinical trials, evaluation of diagnostic tests, and statistical genetics. The course will conclude with a survey of areas of current biostatistical research.
This course is cross-listed with Statistics 449 in the Literature, Science and the Arts department.

BIOSTAT503 Introduction to Biostatistics

Fall term(s)
4 Credit Hour(s)
Instructor(s): Boehnke, Michael L
Offered every year
Prerequisites: Elementary algebra
Description: Fundamental statistical concepts related to the practice of public health: descriptive statistics; probability; sampling; statistical distributions; estimation; hypothesis testing; chi-square tests; simple and multiple linear regression; one-way ANOVA. Use of computer in statistical analysis.
Syllabus for BIOSTAT503 (PDF, 32104 bytes, last modified on Wednesday, June 12, 2013)

BIOSTAT512 Analyzing Longitudinal and Clustered Data Using Statistical Software

Winter term(s)
3 Credit Hour(s)
Instructor(s): Welch, Kathy
Prerequisites: Biostat 503 or Equivalent, , Biostat 520 or equivalent
Description: Longitudinal data sets occur often in a Public Health setting. This course will introduce students to methods for analyzing both clustered and longitudinal data using the statistical software packages SAS and Stata. Models for both continuous and discrete (e.g., binary, count) outcomes will be discussed and illustrated. The course will have one session of lecture and one session of lab per week. The course will be driven primarily by using both software packages to analyze real data sets.
Syllabus for BIOSTAT512 (PDF, 42546 bytes, last modified on Tuesday, February 21, 2012)

BIOSTAT513 Application of Regression Analysis to Public Health Studies

Winter term(s)
3 Credit Hour(s)
Instructor(s): Kidwell, Kelley
Prerequisites: Biostat 503, 553 or Perm. Instr.
Description: Biostat 513 will cover a general overview of linear, logistic, Poisson, and Cox regression. The course will use SPSS as the statistical software.
Syllabus for BIOSTAT513 (PDF, 107338 bytes, last modified on Tuesday, December 04, 2012)

BIOSTAT523 Biostatistical Analysis for Health-Related Studies

Winter term(s)
3 Credit Hour(s)
Instructor(s): Kim, Myra
Prerequisites: BIOSTAT 553; BIOSTAT 503 w/ instructors permission
Description: A second course in applied biostatistical methods and data analysis. Concepts of data analysis and experimental design for health-related studies. Emphasis on categorical data analysis, multiple regression, analysis of variance and covariance.
Syllabus for BIOSTAT523 (PDF, 26716 bytes, last modified on Wednesday, February 06, 2013)

BIOSTAT553 Applied Biostatistics

Fall term(s)
4 Credit Hour(s)
Instructor(s): Tsodikov, Alexander
Prerequisites: Calculus
Description: Fundamental statistical concepts related to the practice of public health: descriptive statistics; probability; sampling; statistical distributions; estimation; hypothesis testing; chi-square tests; simple and multiple linear regression; one-way ANOVA. . Taught at a more advanced mathematical level than Biostat 503. Use of the computer in statistical analysis.
Syllabus for BIOSTAT553 (PDF, 82679 bytes, last modified on Wednesday, June 12, 2013)

BIOSTAT560 Statistical Methods in Epidemiology

Fall term(s)
4 Credit Hour(s)
Instructor(s): Murray, Susan
Prerequisites: Epid 503 or Epid 601 or Epid 600; AND Biostat 523
Description: Statistical methods commonly used in environmental epidemiology. Emphasis on choosing appropriate statistical methods and subsequent interpretation. Topics include probability, measures of association and risk, sample size calculations, SMR and PMR analysis, logistic regression and survival analysis.
Syllabus for BIOSTAT560 (PDF, 43894 bytes, last modified on Wednesday, June 12, 2013)

BIOSTAT578 Practical Projects

Fall, Winter, Spring, Spring-Summer, Summer term(s)
1-4 Credit Hour(s)
Instructor(s): Staff
Prerequisites: NONE
Description: Practical projects in consultation and statistical analysis of data in research studies with health investigators. Course requirements include an approved practical work experience related to Biostatistics in consultation with a faculty advisor. May be elected more than once. Enrollment limited to Biostatistics majors with at least two full terms of prior registration.

BIOSTAT600 Introduction to Biostatistics

Fall term(s)
1 Credit Hour(s)
Instructor(s): Sanchez, Brisa; Welch, Kathy
Prerequisites: Admission to a degree program in Biostatistics
Description: The purpose of this course is to review basic applied statistical concepts and tools and to introduce the SPH computer network and statistical software.
Syllabus for BIOSTAT600 (PDF, 7198 bytes, last modified on Tuesday, February 21, 2012)

BIOSTAT601 Probability and Distribution Theory

Fall term(s)
4 Credit Hour(s)
Instructor(s): Wang, Lu; Li, Yi
Prerequisites: Three terms of calculus
Description: Fundamental probability and distribution theory needed for statistical inference. Probability, discrete and continuous distributions, expectation, generating functions, limit theorems, transformations, sampling theory.
Syllabus for BIOSTAT601 (PDF, 85357 bytes, last modified on Wednesday, June 12, 2013)

BIOSTAT602 Biostatistical Inference

Winter term(s)
4 Credit Hour(s)
Instructor(s): Kang, Hyun Min
Prerequisites: Biostat 601
Description: Fundamental theory that is the basis of inferential statistical procedures. Point and interval estimation, sufficient statistics, hypothesis testing, maximum likelihood estimates, confidence intervals, criteria for estimators, methods of constructing test and estimation procedures.
Syllabus for BIOSTAT602 (PDF, 80741 bytes, last modified on Thursday, January 10, 2013)

BIOSTAT605 Intro to SAS Statistical Programming

Fall term(s)
1 Credit Hour(s)
Instructor(s): Staff
Prerequisites: One course in introductory statistics; Co-requisite Biostat 601 or equivalent or Perm. Instr
Description: This course provides incoming master's students in biostatistics with basic experience in SAS programming for data set creation and manipulation, an introduction to SAS macros, and SAS matrix manipulation.
Syllabus for BIOSTAT605 (PDF, 18613 bytes, last modified on Tuesday, February 21, 2012)

BIOSTAT610 Readings in Biostatistics

Fall, Winter term(s)
1-4 Credit Hour(s)
Instructor(s): Staff
Prerequisites: One of Biostat 503, Biostat 524, Biostat 553 or Biostat 601/Biostat 602
Description: Independent study in a special topic under the guidance of a faculty member. May be elected more than once. Enrollment is limited to biostatistics majors.

BIOSTAT615 Statistical Computing

Fall term(s)
3 Credit Hour(s)
Instructor(s): Jiang, Hui
Prerequisites: None
Description: A survey of key algorithms for statistical computing and its applications in Biostatistics. The course will cover fundamental computational techniques for dynamic programming, sorting, and searching, as well statistical methods for random number generation, numerical integration, function optimization, Markov-Chain Monte Carlo, and the E-M algorithm. Enables students to understand numerical results produced by a computer and to implement their own statistical methods.
Syllabus for BIOSTAT615 (PDF, 30255 bytes, last modified on Tuesday, June 18, 2013)

BIOSTAT617 Theory and Methods of Sample Design (Soc 717 and Stat 580 and SurvMeth 617)

Fall term(s)
3 Credit Hour(s)
Instructor(s): Lepkowski, James M
Prerequisites: Three or more courses in statistics, and preferably a course in methods of survey sampling
Description: Theory underlying sample designs and estimation procedures commonly used in survey practice.
This course is cross-listed with Stats 580 Soc 717 SurvMeth617 in the Rackham department.
Syllabus for BIOSTAT617 (PDF, 46860 bytes, last modified on Tuesday, June 18, 2013)

BIOSTAT619 Clinical Trials

Fall term(s)
2 Credit Hour(s)
Instructor(s): Braun, Thomas
Prerequisites: Biostatistics 601 or equivalent or Perm. Instr. One course Introductory Statistics
Description: This course is designed for individuals with a strong quantitative background that are interested in the scientific, policy, design and management aspects of clinical trials. Topics include types of clinical research, bias and random error, study design, ethics, treatment allocation, randomization and stratification quality control, power and sample size, group sequential monitoring, crossover designs and meta-analysis.
Syllabus for BIOSTAT619 (PDF, 30138 bytes, last modified on Wednesday, June 12, 2013)

BIOSTAT642 Introduction to Functional MRI

Fall term(s)
3 Credit Hour(s)
Instructor(s): Staff
Not offered 2013-2014
Description: This course presents the basic skills to design and analyze functional magnetic resonance imaging (fMRI) experiments. We start by reviewing the basic Matlab and Unix skills necessary to manipulate image data. Next we introduce the principles of MRI and the nature of the Blood Oxygenation Level Dependent (BOLD) effect, including artifacts that corrupt the BOLD signal. We cover blocked and event-related designs, and how to optimize statistical power of design. We cover subject safety.
Syllabus for BIOSTAT642 (PDF, 13970 bytes, last modified on Tuesday, February 21, 2012)

BIOSTAT645 Time Series Analysis with Biomedical Applications

Fall term(s)
3 Credit Hour(s)
Instructor(s): Johnson, Timothy
Not offered 2013-2014
Prerequisites: Biostat 602, Biostat 650 or Perm. Instr
Description: Introduction to statistical time series analysis with an emphasis on frequency domain (spectral) methods and their applications to biomedical problems. Topics include autocorrelation, stationarity, autoregressive and moving average processes, power spectra, periodgrams, spectral estimation, linear filters, complex demodulation, autoregressive integrated moving average (ARIMA) models, cross-correlation, cross-spectra, coherence, time and frequency domain linear regression. The methods will be illustrated in applications to various areas of public health and medical research such as environmental health, electrophysiology, and endocrinology.
Syllabus for BIOSTAT645 (PDF, 23694 bytes, last modified on Tuesday, February 21, 2012)

BIOSTAT646 High Throughput Molecular Genetic and Epigenetic Data Analysis

Winter term(s)
3 Credit Hour(s)
Instructor(s): Sartor, Maureen; Scott, Laura
Prerequisites: Graduate Standing and Statistics 400,Biostatistics 523, or Biostatistics 553 or permission of instructor
Description: The course will cover statistical methods used to analyze data in experimental molecular biology. The course will primarily cover topics relating to gene expression data analysis, but other types of data such as genome sequence and epigenomics data that is sometimes analyzed in concert with expression data will also be covered.
Syllabus for BIOSTAT646 (PDF, 36323 bytes, last modified on Wednesday, August 15, 2012)

BIOSTAT650 Applied Statistics I: Linear Regression

Fall term(s)
4 Credit Hour(s)
Instructor(s): Johnson, Timothy
Prerequisites: BIOSTAT601
Description: Graphical methods, simple and multiple linear regression; simple, partial and multiple correlation; estimation; hypothesis testing, model building and diagnosis; introduction to nonparametric regression; introduction to smoothing methods (e.g., lowess) The course will include applications to real data.
Syllabus for BIOSTAT650 (PDF, 203503 bytes, last modified on Tuesday, August 21, 2012)

BIOSTAT651 Applied Statistics II: Extensions for Linear Regression

Winter term(s)
3 Credit Hour(s)
Instructor(s): Jiang, Hui
Prerequisites: BIOSTAT601 and BIOSTAT650
Description: Introduction to maximum likelihood estimation; exponential family; proportion, count and rate data; generalized linear models; link function; logistic and Poisson regression; estimation; inference; deviance; diagnosis. The course will include application to real data.
Syllabus for BIOSTAT651 (PDF, 90599 bytes, last modified on Tuesday, December 04, 2012)

BIOSTAT652 Design of Experiments

Fall term(s)
3 Credit Hour(s)
Instructor(s): Raghunathan, Trivellore
Prerequisites: Biostat 651
Description: Planning of experiments, use of contrasts in analysis of complete and incomplete block designs. A unified approach to analysis of designs through use of eigen-values and eigenvectors of the association matrix. A-D-E optimality criteria factorial exponents; efficiency of a design, confounding, fractional replication, response-surface designs, rotability criterion, mixture designs, analysis of two-way designs, analysis when blocks are random, applications in biological and biomedical problems.
Syllabus for BIOSTAT652 (PDF, 68766 bytes, last modified on Friday, April 19, 2013)

BIOSTAT653 Applied Statistics III: ANOVA and Linear Mixed Models

Winter term(s)
3 Credit Hour(s)
Instructor(s): Sen, Ananda
Prerequisites: BIOSTAT650 and concurrent enrollment in BIOSTAT651
Description: One-way layout, two-way and higher-way layouts; fixed effects and random effects; multiple comparisons; matching and blocking; balanced and unbalanced designs; weighted least squares; repeated measures; longitudinal and clustered data; linear mixed models; variance components; BLUP; REML. The course will include applications to real data.
Syllabus for BIOSTAT653 (PDF, 61884 bytes, last modified on Tuesday, February 21, 2012)

BIOSTAT664 Special Topics in Biostastics

Fall, Winter term(s)
1-4 Credit Hour(s)
Instructor(s): Song, Peter Xuekun
Prerequisites: Permission of instructor
Description: Master's level seminar designed to provide an extensive review of a number of substantive and methods and skill areas in biostatistics. Readings, discussion, and assignments are organized around issues of mutual interest to faculty and students. Reviews and reports on topics required in the areas selected. May be elected more than once.
Syllabus for BIOSTAT664 (PDF, 82519 bytes, last modified on Wednesday, June 12, 2013)

BIOSTAT665 Statistical Population Genetics

Winter term(s)
3 Credit Hour(s)
Instructor(s): Zoellner, Sebastian
Description: The first half of the course concentrates on classical population genetics. We introduce topics such as Hardy-Weinberg equilibrium, models of selection for populations of infinite size and population subdivision. The second half of the course focuses on coalescent theory, covering migration, changes in population size and recombination. We provide guidelines how these models can be used in to infer population genetic parameters. Finally, some recent results and methods from the population genetic literature are discussed.
Syllabus for BIOSTAT665 (PDF, 37012 bytes, last modified on Tuesday, February 21, 2012)

BIOSTAT666 Statistical Models and Numerical Methods in Human Genetics

Fall term(s)
3 Credit Hour(s)
Instructor(s): Kang, Hyun Min
Prerequisites: Biostat 602 or Perm. Instr.
Description: Introduction to current statistical methods used in human genetics. Topics will include sampling designs in human genetics, gene frequency estimation, the coalescent method for simulation of DNA sequences, linkage analysis, tests of association, detection of errors in genetic data, and the multi-factorial model. The course will include a simple overview of genetic data and terminology and will proceed with a review of numerical techniques frequently employed in human genetics.
Syllabus for BIOSTAT666 (PDF, 35043 bytes, last modified on Tuesday, December 04, 2012)

BIOSTAT675 Survival Time Analysis

Fall term(s)
3 Credit Hour(s)
Instructor(s): Schaubel, Douglas
Prerequisites: Biostat 602 and Biostat 650
Description: Concepts and methods for analyzing survival time data obtained from following individuals until occurrence of an event or their loss to follow-up. Survival time models, clinical life tables, survival distributions, mathematical and graphical methods for evaluating goodness of fit, comparison of treatment groups, regression models, proportional hazards models, censoring mechanisms.
Syllabus for BIOSTAT675 (PDF, 71019 bytes, last modified on Friday, August 10, 2012)

BIOSTAT680 Applications of Stochastic Processes I

Fall term(s)
3 Credit Hour(s)
Instructor(s): Wen, William
Prerequisites: Biostat 601 and Math 450 or equiv
Description: Conditional distributions, probability generating functions, convolutions, discrete and continuous parameter, Markov chains, medical and health related applications.
Syllabus for BIOSTAT680 (PDF, 22891 bytes, last modified on Tuesday, February 21, 2012)

BIOSTAT682 Applied Bayesian Inference

Fall term(s)
3 Credit Hour(s)
Instructor(s): Berrocal, Veronica
Prerequisites: Biostat 602, Biostat 650 and Biostat 651
Description: Introduction to Bayesian Inference. Bayesian large sample inference, relationship with maximum likelihood. Choice of model, including prior distribution. Bayesian approaches to regression generalized linear models, categorical data, and hierarchical models. Empirical Bayes methods. Comparison with frequentist methods. Bayesian computational methods. Assessment of sensitivity to model assumptions. Emphasis on biomedical applications.
Syllabus for BIOSTAT682 (PDF, 75320 bytes, last modified on Tuesday, August 28, 2012)

BIOSTAT685 Elements of Nonparametric Statistics

Winter term(s)
3 Credit Hour(s)
Instructor(s): Zhang, Min
Prerequisites: Biostat 602 or STAT 511, and Biostat 650 or Perm. Instr
Description: First half covers theory and applications of rank and randomization tests: sampling and randomization models, randomization t-test, Wilcoxon rank sum and signed rank tests, Kruskal-Wallis test, asymptotic result under randomization, relative efficiency; second half covers theory and applications of nonparametric regression: smoothing methods, including kernel estimators, local linear regression, smoothing splines, and regression splines, methods for choosing the smoothing parameter, including unbiased risk estimation and cross-validation, introduction to additive models.
Syllabus for BIOSTAT685 (PDF, 44397 bytes, last modified on Monday, December 24, 2012)

BIOSTAT690 Health Applications of Multivariate Analysis

Winter term(s)
3 Credit Hour(s)
Instructor(s): Song, Peter Xuekun
Not offered 2013-2014
Prerequisites: Biostat 650 and Biostat 651 and Math 417 or Perm. Instr.
Description: Techniques of multivariate analysis related to health and biomedical problems. Emphasis on computational techniques and programs with health examples. Tests of significance for one, two or more populations; general linear model; multivariate analyses of variances and covariances; correlation procedures; principal components and discriminant analyses.
Syllabus for BIOSTAT690 (PDF, 92139 bytes, last modified on Tuesday, February 21, 2012)

BIOSTAT695 Analysis of Categorical Data

Fall term(s)
3 Credit Hour(s)
Instructor(s): Sanchez, Brisa
Prerequisites: Biostat 602 and Biostat 660
Description: Regression models for the analysis of categorical data: logistic, probit and complementary log-log models for binomial random variables; log-linear models for cross-classifications of counts; regression models for Poisson rates; and multinomial response models for both nominal and ordinal responses. Model specification and interpretation are emphasized, and model criticism, model selection, and statistical inference are cast within the framework of likelihood based inference.
Syllabus for BIOSTAT695 (PDF, 32684 bytes, last modified on Thursday, August 09, 2012)

BIOSTAT696 Spatial Statistics

Winter term(s)
3 Credit Hour(s)
Instructor(s): Berrocal, Veronica
Prerequisites: BIOSTAT 601, BIOSTAT 602, BIOSTAT 650, BIOSTAT 653
Description: This course will introduce the theory and methods of spatial and spatio-temporal statistics. It will present spatial and spatio-temporal statistical models and will discuss methods for inference on spatial processes within a geostatistical and a hierarchical Bayesian framework.
Syllabus for BIOSTAT696 (PDF, 76275 bytes, last modified on Tuesday, January 08, 2013)

BIOSTAT699 Analysis of Biostatistical Investigations

Winter term(s)
4 Credit Hour(s)
Instructor(s): Elliot, Michael; Braun, Thomas
Prerequisites: Registration for last term of studies to complete MS or MPH
Description: Identifying and solving design and data analysis problems using a wide range of biostatistical methods. Written and oral reports on intermediate and final results of case studies required.
Syllabus for BIOSTAT699 (PDF, 56149 bytes, last modified on Tuesday, February 21, 2012)

BIOSTAT800 Seminar in Biostatistics

Winter term(s)
1 Credit Hour(s)
Instructor(s): Staff
Not offered 2013-2014
Description: Presentations and discussions of current consulting and research problems. May be elected more than once. Enrollment limited to biostatistics majors.

BIOSTAT803 Biostatistics in Cancer Seminar

Fall term(s)
1 Credit Hour(s)
Instructor(s): Taylor, Jeremy
Prerequisites: Perm. Instr.
Description: The purpose of this class is to describe biostatistical research that is occuring in collaboration with cancer researchers, and to provide exposure to the field of cancer research. Activities inlcude seminars on statistical methods in cancer; presentations of cancer research; presentations of articles from statistical literature; discussion of cancer clinical tiral protocals and grant proposals; and visits to research laboratories. Students formally in the training program are expected to enroll in this course every semester. The course is open to students not participating in the training grant. It is open to both PhD and Masters students.
Syllabus for BIOSTAT803 (PDF, 24323 bytes, last modified on Tuesday, December 04, 2012)

BIOSTAT815 Advanced Topics in Computational Statistics

Winter term(s)
3 Credit Hour(s)
Instructor(s): Kang, Hyun Min
Not offered 2013-2014
Prerequisites: Biostat 601, Biostat 602 and Biostat 625 or equiv and proficiency in Fortran or C
Description: Modern numerical analysis for statisticians. Combination of theory and practical computational examples illustrating the current trends in numerical analysis relevant to probability and statistics. Topics choose from numerical linear algebra, optimization theory, quadrature methods, splines, and Markov chains. Emphasis on newer techniques such as quasi-random methods of integration, the EM algorithm and its variants, and hidden Markov chains. Applications as time permits to areas such as genetic and medical imaging.
Syllabus for BIOSTAT815 (PDF, 77346 bytes, last modified on Saturday, December 08, 2012)

BIOSTAT820 Readings in Biostatistics

Fall, Winter, Spring-Summer term(s)
1-4 Credit Hour(s)
Instructor(s): Staff
Description: Students assigned special topics for literature study under guidance of individual faculty members. May be elected more than once. Enrollment limited to biostatistics majors.

BIOSTAT830 Advanced Topics in Biostatistics

Fall, Winter term(s)
1-4 Credit Hour(s)
Instructor(s): Johnson, Timothy; Mukherjee, Bhramar; Abecasis, Goncalo
Description: Advanced training in biostatistical methods primarily for doctoral students. Format will include lectures, readings, presentations and discussions in an area of special interest to students and faculty, such as stopping rules and interim analysis in clinical trials, conditional and unconditional inference and ancillarity, or nonparametric regression.
Syllabus for BIOSTAT830 (PDF, 67113 bytes, last modified on Wednesday, June 13, 2012)

BIOSTAT855 Regression Models in Complex Sample Design Settings (JPSM/MPSM 895)

Fall term(s)
3 Credit Hour(s)
Instructor(s): Elliot, Michael
Not offered 2013-2014
Prerequisites: BIOSTAT617, BIOSTAT650, BIOSTAT651, or instructor permission
Description: This course examines a range of statistical regression analysis techniques for modeling survey data, and presents methods to compensate for design features for complex sample survey data. Course topics include likelihood estimation and testing; application of likelihood methods to linear and generalized linear models, including logistic, probit, generalized (multinomial) logit, Poisson, and negative binomial models; time-to-event (survival analysis) models; regression models for longitudinal data; and propensity score and Bayesian regression modeling.
Syllabus for BIOSTAT855 (PDF, 33416 bytes, last modified on Tuesday, February 21, 2012)

BIOSTAT865 Advanced Statistical Population Genetics

Winter term(s)
3 Credit Hour(s)
Instructor(s): Rosenberg, Noah; Zoellner, Sebastian
Not offered 2013-2014
Description: It is an exciting time for research in population genetics. Technological advances are making it increasingly possible to obtain large numbers of genotypes from individuals in a population, and theoretical and algorithmic advances are improving the prospects for obtaining detailed inferences about populations and their evolutionary history. To make use of these dramatic advances in the field, it is important to understand the processes that act on populations and affect the properties of the genotypes that will eventually be drawn from these populations. In this course, by learning the mathematical models used in population genetics, students will learn how various population-genetic phenomena influence the properties of genetic variation. Students will also gain an understanding of the statistical methods used for analysis of population-genetic data. The course is split into two major sections. The first section covers classical population genetics, including subjects first introduced by RA Fisher and S Wright. We cover Hardy-Weinberg equilibrium, natural selection in infinite and finite populations, stochastic effects in finite populations (drift), recombination and linkage disequilibrium, and admixture and population subdivision. Moreover, we cover the most commonly used models of mutation, such as the infinite sites model and the infinite alleles model. The goal of this section is to give students a broad understanding of the statistical principles underlying population genetics and to provide a connection between these classical results and modern challenges in statistical genetics. In the second section of the course we cover coalescent theory. We introduce the basic coalescent model for constant Wright-Fisher populations. We then introduce commonly used extensions of this model to scenarios with recombination, population expansion and population subdivision. We introduce methods of parameter inference based on these models, including both simple method-of-moments estimates as well as more sophisticated Monte-Carlo based estimation methods. The goal of this section is to give students the ability to design realistic simulation algorithms and perform population genetic inference. Classes on population structure and population admixture (~4) will be taught by Noah Rosenberg. In the biweekly homeworks, we expect the students to be able to apply and extend the presented theory. Early in the course, each student will select a topic for a project; the student is expected to work on this project throughout the semester and to give at the end of the semester a written project report and a 20-minute presentation on the results of his analysis. Typical projects are " Simulate a model of rare variants under mutation-selection balance and estimate power for rare variants testing methods. " Calculate the contribution of low frequency variants to heritability in structured populations " Perform a principal components analysis on genetic data " Explore recent resequencing data for signs of natural selection.
Course Goals: See course description
Competencies: See course description

BIOSTAT866 Advanced Topics in Genetic Modeling

Fall term(s)
3 Credit Hour(s)
Instructor(s): Abecasis, Goncalo
Not offered 2013-2014
Prerequisites: Biostat 601, Biostat 602, Biostat 666 or Perm. Instr.
Description: Advanced topics in quantitative genetics with emphasis on models for gene mapping, pedigree analysis, reconstruction of evolutionary trees, and molecular genetics experiments, computational mathematics, and statistical techniques such as Chen-Stein Poisson approximations, hidden Markov chains, and the EM algorithm introduced as needed.

BIOSTAT870 Analysis of Repeated Measurements

Fall term(s)
3 Credit Hour(s)
Instructor(s): Zhang, Min
Prerequisites: Math 417, Biostat 602, Biostat 651 and one of Biostat 690, Biostat 851, or Biostat 890
Description: Mixed model analysis of variance; multivariate profile analysis; linear mixed effects models with unbalanced designs, time-varying covariates, and structured covariance matrices; maximum likelihood (ML), restricted maximum likelihood (REML), and Bayes estimation and inference; nonlinear mixed effects models.
Syllabus for BIOSTAT870 (PDF, 33609 bytes, last modified on Monday, December 24, 2012)

BIOSTAT875 Advanced Topics in Survival Analysis

Winter term(s)
3 Credit Hour(s)
Instructor(s): Murray, Susan
Prerequisites: Biostat 675
Description: Lectures and readings from the literature on advanced topics in survival analysis. Covers regression for censored data, general event-history data and models, competing risks. Statistical, mathematical, and probabilistic tools used in survival analysis are extended for these general problems.

BIOSTAT880 Statistical Analysis With Missing Data

Winter term(s)
3 Credit Hour(s)
Instructor(s): Wang, Lu
Prerequisites: Biostat 602 and 651, and at least one of Biostat 690, Biostat 851, Biostat 890, or Biostat 895 or Perm Inst.
Description: Statistical analysis of data sets with missing values. Pros and cons of standard methods such as complete-case analysis, imputation. Likelihood-based inference for common statistical problems, including regression, repeated-measures analysis, and contingency table analysis. Stochastic censoring models for nonrandom nonresponse. Computational tools include the EM algorithm, the Gibbs’ sampler, and multiple imputation.
Syllabus for BIOSTAT880 (PDF, 157788 bytes, last modified on Tuesday, December 18, 2012)

BIOSTAT885 Nonparametric Statistics

Winter term(s)
3 Credit Hour(s)
Instructor(s): Song, Peter Xuekun
Not offered 2013-2014
Prerequisites: Biostat 601/602 or Perm. Instr.
Description: Theory and techniques of nonparametrics and robustness. M-estimation, influence function, bootstrap, jackknife, generalized additive models, smoothing techniques, penalty functions, projection pursuit, CART.
Syllabus for BIOSTAT885 (PDF, 77938 bytes, last modified on Tuesday, November 06, 2012)

BIOSTAT895 Analysis of Multivariate Categorical Data

Fall term(s)
3 Credit Hour(s)
Instructor(s): Song, Peter Xuekun
Not offered 2013-2014
Prerequisites: Biostat 651 and Biostat 695 or Perm. Instr.
Description: Probability models for two-way tables; multi-factor, multi-response framework; product multinomial distribution theory; Taylor series estimates of variance, weighted least squares and Wald statistics; constraint equations; models for characterizing interactions; step-wise variable selection; factorial designs with multinomial responses; repeated measurement experiments; log-linear models; paired-choice and bioassay experiments; life-table models.

BIOSTAT896 Spatial Statistics

Winter term(s)
3 Credit Hour(s)
Instructor(s): Berrocal, Veronica
Not offered 2013-2014
Prerequisites: BIOSTAT 601, BIOSTAT 602, BIOSTAT 650, BIOSTAT 653
Description: This course will introduce the theory and methods of spatial and spatio-temporal statistics. It will present spatial and spatio-temporal statistical models and will discuss methods for inference on spatial processes within a geostatistical and a hierarchical Bayesian framework.
Syllabus for BIOSTAT896 (PDF, 76273 bytes, last modified on Tuesday, January 08, 2013)

BIOSTAT990 Dissertation/Pre-Candidacy

Fall, Winter, Spring-Summer term(s)
1-8 Credit Hour(s)
Instructor(s): Staff
Prerequisites: (1-8 Full term, 1-4 Half term)
Description: Election for dissertation work by doctoral student not yet admitted to status as a candidate.

BIOSTAT995 Dissertation Research for Doctorate in Philosophy

Fall, Winter, Spring-Summer term(s)
1-8 Credit Hour(s)
Instructor(s): Staff
Prerequisites: Admission to Doctoral Program(1-8 Full term, 1-4 Half term)
Description: Election for dissertation work by doctoral student who has been admitted to status as a candidate.

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