Detailed course offerings (Time Schedule) are available for
To see the detailed Instructor Class Description, click on the underlined instructor name following the course description.
BIOST 111 Lectures in Applied Statistics (1) NW
Weekly lectures illustrating the importance of statisticians in a variety of fields, including medicine and the biological, physical, and social sciences. Credit/no credit only. Offered: jointly with STAT 111; Sp.
BIOST 310 Biostatistics for the Health Sciences (4) QSR Hughes
Introduction to statistical methods for students panning on majoring in health sciences. Uses case studies and examples from popular and scientific literature to introduce topics such as data description, study design, screening, estimation hypothesis testing, categorical data analysis, and regression. Emphasizes concepts and interpretation rather than computation or theory. Offered: W.
BIOST 499 Undergraduate Research (*)
Supervised reading programs; library and field research; special projects. Credit/no-credit only.
BIOST 502 Introduction to Statistics in Health Sciences (4)
Description and examples of common concepts in biostatistics. Probability, point and confidence interval estimation, hypothesis testing including two-sample and paired t and chi-square tests, introduction to simple linear regression. Emphasizes applications in health sciences. Offered: S.
BIOST 503 Application of Statistics to Health Sciences ([0-3]-, max. 3)
Standard statistical techniques presented with examples drawn from the health sciences literature. Critical interpretation of research results, and introduction to the computer for data processing and statistical analysis. Prerequisite: BIOST 502 or equivalent. Offered: S.
BIOST 508 Biostatistical Reasoning for the Health Sciences (4)
Provides a broad overview of biostatistical methods, emphasizing interpretation and concepts rather than computation or mathematical details. Introduces basic concepts of study design, data summaries and presentation, statistical inference (including hypothesis testing, p-values, and confidence intervals) and modeling approaches such as regression analysis. No hands-on analysis, nor use of statistical packages.
BIOST 510 Biostatistics in Dentistry (3)
Introduction to concepts and methods of descriptive and inferential statistics with applications in dentistry emphasized. Topics include comparison of means and proportions, hypothesis testing, confidence intervals, non-parametric methods, linear regression, and correlation. Prerequisite: enrollment in School of Dentistry or permission of instructor. Offered: jointly with DPHS 568.
BIOST 511 Medical Biometry I (4)
Presentation of the principles and methods of data description and elementary parametric and nonparametric statistical analysis. Examples are drawn from the biomedical literature, and real data sets are analyzed by the students after a brief introduction to the use of standard statistical computer packages. Statistical techniques covered include description of samples, comparison of two sample means and proportions, simple linear regression and correlation. Offered: A.
BIOST 512 Medical Biometry II (4)
Multiple regression, analysis of covariance, and an introduction to one-way and two-way analyses of variance: including assumptions, transformations, outlier detection, dummy variables, and variable selection procedures. Examples drawn from the biomedical literature with computer assignments using standard statistical computer packages. Prerequisite: either BIOST 511 or BIOST 517, or equivalent. Offered: W.
BIOST 513 Medical Biometry III (4)
Analysis of categorical data including two sample methods, sets of 2 x 2 tables, R x C tables, and logistic regression. Classification and discrimination techniques. Survival analysis including product limit estimates and the Cox proportional hazards model. Prerequisite: BIOST 512 or permission of instructor. Offered: Sp.
Instructor Course Description: Norbert David Yanez Iii
BIOST 514 Biostatistics I (4)
Presentation of principles and methods of data description; graphics; point, confidence interval estimation; hypothesis testing; relative risk; odds ratio; Mantel-Haenszel; chi-square test. Examples drawn from biomedical literature; real-data sets analyzed using statistical computer packages. Prerequisite: biostatistics majors or permission of instructor. Offered: A.
BIOST 515 Biostatistics II (4)
Introduction to linear models; multiple regression, correlation; residual analysis; dummy variables; analysis of covariance; one-, two-way analysis of variance; randomized blocks; fixed, random effects (repeated measure, factorial designs); multiple comparisons . Real biomedical data sets analyzed. Prerequisite: BIOST 514, biostatistics major, or permission of instructor. Offered: W.
BIOST 516 Statistical Methods in Genetic Epidemiology (3)
Theory and application of statistical techniques used in genetic epidemiology. Includes discussion of association studies, linkages, and segregation analyses. Examples stressed with reference to assumptions and limitations. Prerequisite: either BIOST 513 or BIOST 518; PHG 511/EPI 517, or permission of instructor. Offered: jointly with EPI 516/PHG 519.
Instructor Course Description: Stephanie Monks
BIOST 517 Applied Biostatistics I (4)
Introduction to the analysis of biomedical data. Descriptive and inferential statistical analysis for discrete, continuous, and right-censored random variables. Analytic methods based on elementary parametric and non-parametric models for one sample; two sample (independent and paired), stratified sample, and simple regression problems. Offered: A.
BIOST 518 Applied Biostatistics II (4)
Multiple regression for continuous, discrete, and right-censored response variables, including dummy variables, transformations, and interactions. Introduction to regression with correlated outcome data. Model and case diagnostics. Computer assignments using real data and standard statistical computer packages. Prerequisite: BIOST 517 or permission of instructor. Offered: W.
BIOST 519 Advanced Epidemiologic Methods (4)
Introduces advanced epidemiologic methods, including casual modeling, inverse probability weighting, propensity scores, sensitivity analysis, imputation for missing data, approaches to multiple comparisons, Bayesian adjustment of risk estimates, recursive portioning, and modeling for prediction. Prerequisite: EPI 512; EPI 513; EPI 514; EPI/BIOST 536. Offered: jointly with EPI 515; A.
BIOST 524 Design of Medical Studies (3)
Design of medical studies, with emphasis on randomized controlled clinical trials. Bias elimination, controls, treatment assignment and randomization, precision, replication, power and sample size calculations, stratification, and ethics. Suitable for graduate students in biostatistics and for research-oriented graduate students in other scientific fields. Prerequisite: BIOST 511 or equivalent, and one of BIOST 513, BIOST 518, STAT 421, STAT 423, STAT 512, or EPI 512; or permission of instructor. Offered: jointly with STAT 524; Sp.
BIOST 527 Nonparametric Regression and Classification (3)
Covers techniques for smoothing and classification including spline models, kernel methods, generalized additive models, and the averaging of multiple models. Describes measures of predictive performance, along with methods for balancing bias and variance. Prerequisite: either STAT 502 and STAT 504 or BIOST 514 and BIOST 515. Offered: jointly with STAT 527; Sp.
BIOST 529 Sample Survey Techniques (3)
Design and implementation of selection and estimation procedures. Emphasis on human populations. Simple, stratified, and cluster sampling; multistage and two-phase procedures; optimal allocation of resources; estimation theory; replicated designs; variance estimation; national samples and census materials. Prerequisite: either STAT 421, STAT 423, STAT 504, QMETH 500, BIOST 511, or BIOST 517, or equivalent or permission of instructor. Offered: jointly with CS&SS 529/STAT 529.
Instructor Course Description: Jean-Yves Pip Courbois
BIOST 531 Statistical Methods for Analysis with Missing Data (3) Chan
Covers statistical methods for the analysis of missing data, including likelihood-based, weighted GEE, multiple imputation, and Bayesian approaches. Uses computational tools such as EM algorithm and Gibbs' sampler. Covers both ignorable and non-ignorable missing-data mechanisms as well as cross-sectional and longitudinal study designs. Primarily uses data arising from epidemiologic studies. Offered: jointly with EPI 531; W.
BIOST 533 Theory of Linear Models (3)
Examines model structure; least squares estimation; Gauss-Markov theorem; central limit theorems for linear regression; weighted and generalized least squares; fixed and random effects; analysis of variance; blocking and stratification; and applications in experimental design. Prerequisite: STAT 421 or STAT 423; and STAT 513, BIOST 515, and a course in matrix algebra. Offered: jointly with STAT 533; Sp.
BIOST 534 Statistical Computing (3)
Introduction to scientific computing. Includes programming tools, modern programming methodologies, (modularization, object oriented design), design of data structures and algorithms, numerical computing and graphics. Uses C++ for several substantial scientific programming projects. Prerequisite: experience with programming in a high level language. Offered: jointly with STAT 534; Sp.
BIOST 536 Categorical Data Analysis in Epidemiology (4)
Summary of univariate categorical data analysis; iIntroduction to multivariate analysis of categorical epidemiologic and health sciences data using multiplicative models. Experience at interpretation; familiarity with available softwareprograms gained by analysis of bona fide data and critiques of published analyses appearing in literature. Prerequisite: BIOST 515; EPI 513 and either BIOST 513 or BIOST 518; or permission of instructor. Offered: jointly with EPI 536; A.
Instructor Course Description: Norman Breslow
BIOST 537 Survival Data Analysis in Epidemiology (4)
Introduction to multivariate analysis of survival data using multiplicative models. Application to epidemiologic and health sciences studies. Familiarity with interpretation and available softwarecomputer programs gained by analysis of bona fide sets of data and critiques of published analyses appearing in the literature. Prerequisite: BIOST 536 or permission of instructor. Offered: jointly with EPI 537; W.
Instructor Course Description: Norman Breslow
BIOST 540 Correlated Data Regression (3)
Introduction to regression modeling of longitudinal and clustered data from epidemiology and health sciences. Interpretation and familiarity with software gained by analysis of data and critiques of published analyses. Prerequisite: Either BIOST 513, BIOST 515, BIOST 518, BIOST 536, or permission of instructor. Offered: Sp.
Instructor Course Description: Kenneth M. Rice Brian Leroux Norman Breslow Norbert David Yanez Iii
BIOST 550 Statistical Genetics I: Mendelian Traits (3)
Mendelian genetic traits. Population genetics; Hardy-Weinberg, allelic variation, subdivision. Likelihood inference, information and power; latent variables and EM algorithm. Pedigree relationships and gene identity. Meiosis and recombination. Linkage detection. Multipoint linkage analysis. Prerequisite: STAT 390 and STAT 394, or permission of instructor. Offered: jointly with STAT 550; Sp.
BIOST 551 Statistical Genetics II: Quantitative Traits (3)
Statistical basis for describing variation in quantitative traits. Decomposition of trait variation into components representing genes, environment and gene-environment interaction. Methods of mapping and characterizing quantitative trait loci. Prerequisite: STAT/BIOST 550; STAT 423 or BIOST 515; or permission of instructor. Offered: jointly with STAT 551; A.
BIOST 552 Statistical Genetics III: Design and Analysis (3)
Overview of probability models, inheritance models, penetrance. Association and linkage. The lod score method. Affected sib method. Fitting complex inheritance models. Design mapping studies; multipoint, disequilibrium, and fine-scale mapping. Ascertainment. Prerequisite: STAT/BIOST 551; GENOME 371; or permission of instructor. Offered: jointly with STAT 552; W.
BIOST 555 Statistical Methods for Spatial Epidemiology (3)
Motivates the need for, and describes methods for the analysis of spatially indexed epidemiological data. Covers four major topics: clustering and cluster detection, disease mapping, spatial regression, and an introduction to geographical information systems. Considers both point-references and spatially aggregated data. Offered: jointly with EPI 555; W.
BIOST 570 Advanced Regression Methods for Independent Data (3)
Covers linear models, generalized linear and non-linear regression, and models. Includes interpretation of parameters, including collapsibility and non-collapsibility, estimating equations; likelihood; sandwich estimations; the bootstrap; Bayesian inference: prior specification, hypothesis testing, and computation; comparison of approaches; and diagnostics. Prerequisite: STAT 512 and STAT 513;BIOST/STAT 533 or STAT 421/STAT 502 and STAT 423/STAT 504; a course in matrix algebra. Offered: jointly with STAT 570; A.
BIOST 571 Advanced Regression Methods for Dependent Data (3)
Covers longitudinal data models, generalized linear and non-linear mixed models; marginal versus conditional models; generalized estimating equations, likelihood-based inference, REML, BLUP, and computation of integrals; Bayesian inference: Markov chain Monte Carlo; covariance models, including models for split plot designs; comparison of approaches; and diagnostics. Prerequisite: BIOST570/STAT 570. Offered: jointly with STAT 571; W.
BIOST 572 Advanced Regression Methods: Project (3)
Student presentations and discussion on selected methodological research articles focusing on regression modeling. Prerequisite: STAT 571. Offered: jointly with STAT 572; Sp.
BIOST 573 Statistical Methods for Categorical Data (3)
Advanced topics in generalized linear models and the analysis of categorical data: overdispersion, quasilikelihood, parameters in link and variance functions, exact conditional inference, random effects, saddlepoint approximations. Credit/no-credit only. Prerequisite: BIOST 571 and STAT 582. Offered: jointly with STAT 573; Sp.
Instructor Course Description: Norman Breslow
BIOST 574 Multivariate Statistical Methods (3)
Use of multivariate normal sampling theory, linear transformations of random variables, one- and two-sample tests, profile analysis, partial and multiple correlation, multivariate ANOVA and least squares, discriminant analysis, principal components, factor analysis, robustness, and some special topics. Some computer use included. Prerequisite: BIOST 570 or permission of instructor. Offered: jointly with STAT 574.
BIOST 576 Statistical Methods for Survival Data (3)
Statistical methods for censored survival data arising from follow-up studies on human or animal populations. Parametric and nonparametric methods, Kaplan-Meier survival curve estimator, comparison of survival curves, log-rank test, regression models including the Cox proportional hazards model, competing risks. Prerequisite: STAT 581 and either BIOST 515, STAT 473, or equivalent. Offered: jointly with STAT 576.
Instructor Course Description: Ying Qing Chen
BIOST 577 Advanced Design and Analysis of Experiments (3)
Concepts important in experimental design and analyzing data from planned experiments. Multi-way layouts, randomized block designs, incomplete block designs, Lating and Graeco-Latin squares, factorial and fractional designs, split-plot designs, optimal design theory, response surface experiments. Prerequisite: either BIOST 515, BIOSTAT 533, STAT 502, STAT 504, STAT 533, or permission of instructor. Offered: jointly with STAT 577.
BIOST 578 Special Topics in Advanced Biostatistics (*, max. 30)
Advanced-level topics in biostatistics offered by regular and visiting faculty. Prerequisite: permission of instructor. Offered: jointly with STAT 578; AWSpS.
Instructor Course Description: Xiao-Hua Andrew Zhou Kenneth M. Rice Michal Kulich Margaret Pepe Elizabeth A. Sheppard Norbert David Yanez Iii
BIOST 579 Data Analysis and Reporting (2)
Analysis of real data to answer scientific questions. Common data-analytic problems. Sensible approaches to complex data. Graphical and tabular presentation of results. Writing reports for scientific journals, research collaborators, consulting clients. Graduate standing in statistics or biostatistics or permission of instructor. Offered: jointly with STAT 579; AWSp.
Instructor Course Description: Norman Breslow
BIOST 580 Seminar in Biostatistics (*, max. 30)
Presentation and discussion of special topics and research results in biostatistics. Speakers include resident faculty, visiting scientists, and advanced graduate students. Offered: AWSp.
Instructor Course Description: Kenneth M. Rice
BIOST 581 Statistical Genetics Seminar (1, max. 30)
Presentations and discussion of special topics and research results in statistical genetics. Students, posdocs, and faculty present their work and papers from the literature. Credit/no-credit only. Offered: AWSp.
BIOST 582 Student Seminar (1, max. 30)
Student seminar series for collaboration, exchange of ideas, and exposure to different stages of performing independent research. Encourages both students and faculty to give presentations including RA work, extended class projects, master's theses, dissertation progress, data analysis, practice talks, and journal articles. Credit/no-credit only. Offered: AWSpS.
BIOST 590 Biostatistical Consulting (*)
Training in consulting on the biostatistical aspect of research problems arising in the biomedical field. Students, initially under the close supervision of a faculty member, participate in discussions with investigators leading to the design and/or the analysis of a quantitative investigation of a problem. With experience, independent associations of student and research worker are encouraged, with subsequent review by faculty of resulting design and analysis. Prerequisite: permission of instructor. Offered: AWSpS.
BIOST 595 Biostatistics Master's Practicum (1-12, max. 12)
Supervised practice experience providing students an opportunity to learn how biostatistics is applied in a public health setting and in the formation of public health policy. Prerequisite: BIOST 514; BIOST 515; BIOST 536; BIOST 537.
BIOST 600 Independent Study or Research (*-)
Instructor Course Description: Kenneth M. Rice
BIOST 700 Master's Thesis (*-)
BIOST 800 Doctoral Dissertation (*-)