COURSE INFORMATION
Biostatistics
BIO111 Introduction to Programming in SAS
WinterSession
Dr. T. Fenton (P), Dr. M. Pagano (S)
1.25 credits
Lectures and Laboratories. Six 4-hour sessions combining both.
Provides an overview in the use of SAS to prepare data for statistical analysis. The focus is on database management and programming problems. Basic issues in each of these areas are discussed in the context of introducing the specific skills required to use SAS effectively.
Course Note: Credit is given for only one of BIO 111 or BIO 113; The course meets January 8, 9, 10, 15, 16, 17.
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.
Course Evaluations
BIO113 Introduction to Data Management and Programming in SAS
Fall 1
Ms. L. Allred (P); Dr. M. Pagano (S)
2.5 credits
Lectures, laboratories. Two 2-hour sessions each week. Two 1-hour lab each week.
Provides intensive instruction in the use of SAS to prepare data for statistical analysis. The focus is on database management and programming problems. Basic issues in each of these areas are discussed in the context of teaching the specific skills required to use SAS effectively.
Course Note: Credit is given for only one of BIO 111 or BIO 113; BIO 200, BIO 201, or BIO 202 and BIO 203, or signature of instructor required; lab time follows each course session for one hour.
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.
Course Evaluations
BIO200 Principles of Biostatistics
Fall
Dr. D. Wypij
5 credits
Lectures, laboratories. Two 1-hour sessions each week. One 2-hour lab each week.
Lectures and laboratory exercises acquaint the student with the basic concepts of biostatistics and their applications and interpretation. The computer is used throughout the course. Topics include descriptive statistics, graphics, diagnostic tests, probability distributions, inference, tests of significance, association, linear and logistic regression, life tables, and survival analysis.
Course Note: Credit is given for only one of BIO 200, BIO 201; this course cannot be counted as part of the credit requirement for a major or minor doctoral field course; course restricted to students not eligible for BIO 201. Other students allowed with signature of course instructor, if space permits; course enrollment is limited to 150 students; lab or section times to be announced at first meeting. (5.06)
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.
Course Evaluations
BIO200R Principles of Biostatistics Repeat
Spring
Dr. D. Wypij
2.5 credits
Independent Study
Open only to students who have failed the core course, and must repeat it. Students must sign up for the section with the instructor from whom they took the original course.
Course Note: Completed independent study contract is required at the time of registration; pass/fail only; signature of instructor required.
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.
Course Evaluations
BIO201 Introduction to Statistical Methods
Fall
Dr. K. Gauvreau
5 credits
Lectures, laboratories. Two 1.5-hour sessions each week. One 2-hour lab each week.
Covers basic statistical techniques that are important for analyzing data arising from epidemiology, environmental health and biomedical and other public health-related research. Major topics include descriptive statistics, elements of probability, introduction to estimation and hypothesis testing, nonparametric methods, techniques for categorical data, regression analysis, analysis of variance, and elements of study design. Applications are stressed. Designed as an alternate to BIO200, for students desiring more emphasis on theoretical developments. Background in algebra and calculus strongly recommended.
Course Note: Credit is given for only one of BIO200 or BIO201; this course cannot be counted as part of the credit requirement for a major or minor doctoral field course; course restricted to students enrolled in DBS, EH, EPI, NUT, MPH/QM programs, and SHDH doctoral students. Other students allowed with signature of course instructor if space permits; lab or section times to be announced at first meeting.
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.
Course Evaluations
BIO201R Introduction to Statistical Methods
Spring
Dr. K. Gauvreau
2.5 credits
Independent Study
Open only to students who have failed the core course, and must repeat it. Students must sign up for the section with the instructor from whom they took the original course.
Course Note: Completed independent study contract is required at the time of registration; pass/fail only; signature of instructor required.
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.
Course Evaluations
BIO202 Principles of Biostatistics I
Summer 1
Dr. M. Testa
2.5 credits
Lectures, laboratories. Five 2-hour sessions and five 2-hour labs each week.
This course is the first part of introductory biostatistics and acquaints the student with the basic concepts and methods of biostatistics, their applications, and their interpretation. The material covered includes data presentation, numerical summary measures, rates and standardization, and life tables. Probability is introduced to quantify uncertainty, especially as it pertains to diagnostic and screening methods. Also covered are sampling distributions so that students may be introduced to confidence intervals and hypothesis testing. The computer is used throughout the c ourse, and the student will gain familiarity with the software package STATA.
Course Note: Requires a basic knowledge of mathematics and familiarity with use of personal computers. Students taking BIO202 and BIO203 will not be given credit for BIO200 or BIO201. (rev. 10.06)
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.
Course Evaluations
BIO203 Principles of Biostatistics II
Summer 2
Dr. H. Jiang
2.5 credits
Lectures, laboratories. Five 2-hour sessions each week and five 2-hour labs each week.
This course is the second part of introductory biostatistics; it continues to explore inference in greater depth. Lectures and laboratory exercises will emphasize applied data analysis, building upon the fundamentals emphasized in BIO 202. Topics covered include the comparison of two means, analysis of variance, non-parametric methods, inference on proportions, contingency tables, multiple 2 X 2 tables, correlation, simple regression, multiple regression and logistic regression, analysis of survival data, and sampling theory. The computer is used throughout the course, and the student will gain more familiarity with STATA.
Course Note: BIO 202 is required; Students who take BIO202 and BIO 203 will not be given credit for BIO200 or BIO201. (rev. 10.06)
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.
Course Evaluations
BIO206 Introductory Statistics for Medical Research
Summer 1
Dr. E. J. Orav
2.5 credits
Lectures. Five 2-hour sessions each week.
Introduces basic biostatistical techniques with an emphasis on applications to clinical research. Topics include probability and
statistics, hypothesis testing, confidence intervals, non-parametrics, and power calculations.
Course Note: Designed primarily for participants in the Program in Clinical Effectiveness; no auditors. (rev. 10.06)
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.
Course Evaluations
BIO207 Statistics for Medical Research II
Summer 2
Dr. G. Reed (P), Dr. E.J. Orav (S)
2.5 credits
Lectures. Five 2-hour sessions each week.
Presents additional biostatistical techniques that commonly appear in the analysis of clinical databases and trials. Topics include contingency table analyses, log-rank tests, paired and matched analyses, analysis of variance and multiple comparisons procedures.
Course Note: BIO 206 required; no auditors. (rev. 10.06)
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.
Course Evaluations
BIO208 Statistics for Medical Research, Advanced
Summer 2
Dr. E. J. Orav
2.5 credits
Lectures. Five 2-hour sessions each week.
Presents additional biostatistical techniques that commonly appear in the analysis of clinical databases and trials. This course will move at a faster pace than the alternative BIO 207 while covering all of the same topics (contingency tables, log-rank tests, paired and matched analyses, analysis of variance and multiple comparisons procedures). In addition, linear and logistic regression will be introduced.
Course Note: BIO 206 required; no auditors. (rev. 10.06)
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.
Course Evaluations
BIO209 Statistics for Medical Research, Translational
Summer 2
TBA
2.5 credits
Lectures. Five 2-hour sessions each week.
Presents additional biostatistical techniques that are most relevant to researchers involved with designed experiments. Topics include contingency tables, paired analyses, simple analysis of variance, multiple comparisons procedures, two-way analysis of variance, and simple repeated measures analysis of variance.
Course Note: BIO 206 required; no auditors.
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.
Course Evaluations
BIO210 The Analysis of Rates and Proportions
Spring
Dr. J. Ware
5 credits
Lectures, laboratories. Two 1.5-hour sessions each week. One 1.5-hour lab each week.
Emphasizes concepts and methods for analysis of data which are categorical, rate-of-occurrence (e.g., incidence rate), and time-to-event (survival duration). Stresses applications in epidemiology, clinical trials, and other public health research. Topics include measures of association, 2x2 tables, stratification, matched pairs, logistic regression, model building, analysis of rates, and survival data analysis using proportional hazards models.
Course Note: BIO 200, or BIO 201, or BIO 202 and BIO 203, or BIO 206 and one of BIO 207, BIO 208, or BIO 209, or signature of instructor required; lab or section times to be announced at first meeting. (5.06)
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.
Course Evaluations
BIO210 The Analysis of Rates and Proportions
Fall
Dr. G. DiRienzo
5 credits
Lectures, laboratories. Two 1.5-hour sessions each week. One 1.5-hour lab each week.
Emphasizes concepts and methods for analysis of data which are categorical, rate-of-occurrence (e.g., incidence rate), and time-to-event (survival duration). Stresses applications in epidemiology, clinical trials, and other public health research. Topics include measures of association, 2x2 tables, stratification, matched pairs, logistic regression, model building, analysis of rates, and survival data analysis using proportional hazards models.
Course Note: BIO 200, or BIO 201, or BIO 202 and BIO 203, or BIO 206 and one of BIO 207, BIO 208, or BIO 209, or signature of instructor required; lab or section times to be announced at first meeting. (5.06)
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.
Course Evaluations
BIO211 Regression and Analysis of Variance in Experimental Research
Fall
Dr. C. Hu
5 credits
Lectures, laboratories. Two 1.5-hour sessions each week; one 1-hour lab each week.
Covers analysis of variance and regression, including details of data-analytic techniques and implications for study design. Also included are probability models and computing. Students learn to formulate a scientific question in terms of a statistical model, leading to objective and quantitative answers.
Course Note: BIO 200, or BIO 201, or BIO 202 and BIO 203, or BIO 206 and one of BIO 207, BIO 208, or BIO 209, or signature of instructor required; lab or section times to be announced at first meeting. (5.06)
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.
Course Evaluations
BIO212 Survey Research Methods In Community Health
Spring
Dr. T. Mangione (P), Dr. L. Ryan (S)
2.5 credits
Lectures. One 2-hour session each week.
Covers research design, sample selection, questionnaire construction, interviewing techniques, the reduction and interpretation of data, and related facets of population survey investigations. Focuses primarily on the application of survey methods to problems of health program planning and evaluation. Treatment of methodology is sufficiently broad to be suitable for students who are concerned with epidemiological, nutritional, or other types of survey research. (5.06)
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.
Course Evaluations
BIO213 Applied Regression for Clinical Research
Fall
Dr. E. J. Orav
5 credits
Lectures. Two 2-hour sessions each week. One 1.5-hour lab each week.
This course will introduce students involved with clinical research to the practical application of multiple regression analysis. Linear regression, logistic regression and proportional hazards survival models will be covered, as well as general concepts in model selection, goodness-of-fit, and testing procedures. Each lecture will be accompanied by a data analysis using SAS and a classroom discussion of the results. The course will introduce, but will not attempt to develop the underlying likelihood theory. Background in SAS programming ability required.
Course Note: BIO 200, or BIO 201, or BIO 202 and BIO 203, or BIO 206 and one of BIO 207, BIO 208, or BIO 209, or signature of instructor required; lab or section times to be announced at first meeting. (5.06)
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.
Course Evaluations
BIO214 Principles of Clinical Trials
Spring 1
Dr. S. Lagakos
2.5 credits
Lectures. Two 2-hour sessions each week.
Designed for individuals interested in the scientific, policy, and management aspects of clinical trials. Topics include types of clinical research, study design, treatment allocation, randomization and stratification, quality control, sample size requirements, patient consent, and interpretation of results. Students design a clinical investigation in their own field of interest, write a proposal for it, and critique recently published medical literature.
Course Note: BIO 200, or BIO 201, or BIO202 and BIO203, or BIO206 and one of BIO 207, BIO 208 or BIO 209, or signature of instructor required. (5.06)
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.
Course Evaluations
BIO214 Principles of Clinical Trials
Summer 2
Dr. K. Stanley, Dr. R. Gelber
2.5 credits
Lectures. Five 2-hour sessions each week.
Designed for individuals interested in the scientific, policy, and management aspects of clinical trials. Topics include types of clinical research, study design, treatment allocation, randomization and stratification, quality control, sample size requirements, patient consent, and interpretation of results. Students design a clinical investigation in their own field of interest, write a proposal for it, and critique recently published medical literature.
Course Note: Signature of instructor required. (rev. 10.06)
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.
Course Evaluations
BIO222 Basics of Statistical Inference
Fall
Dr. P. Williams
5 credits
Lectures, laboratories. Two 1.5 hour-sessions each week. One 2-hour lab each week.
This course will provide a basic, yet thorough introduction to the probability theory and mathematical statistics that underlie many of the commonly used techniques in public health research. Topics to be covered include probability distributions (normal, binomial, Poisson), means, variances and expected values, finite sampling distributions, parameter estimation (method of moments, maximum likelihood), confidence intervals, hypothesis testing (likelihood ratio, Wald and score tests). All theoretical material will be motivated with problems from epidemiology, biostatistics, environmental health and other public health areas. This course is aimed towards second year doctoral students in fields other than Biostatistics. Background in algebra and calculus required.
Course Note: One intermediate level biostatistics course such as BIO 210, or BIO 211, or signature of the instructor required; lab or section times to be announced at first meeting. (5.06)
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.
Course Evaluations
BIO223 Applied Survival Analysis
Spring
R. Betensky
5 credits
Lectures. Two 2-hour sessions each week. One 1-hour optional lab each week.
This course will cover topics in both discrete data analysis (25% of class) and applied survival analysis (75% of class). The course will begin with a review of sampling plans and contingency table for discrete data. Further topics in discrete data analysis will include logistic regression, exact inference, and conditional logistic regression. This short survey of discrete data topics will provide a natural transition to analysis of survival data. Survival topics include: hazard, survivor, and cumulative hazard functions, Kaplan-Meier and actuarial estimation of the survival distribution, comparison of survival using log rank and other tests, regression models including the Cox proportional hazards model and accelerated failure time model, adjustment for time-varying covariates, and use of parametric distributions (exponential, Weibull) in survival analysis. Class material will include presentation of statistical methods for estimation and testing, along with current software (SAS, Stata, Splus) for implementing analyses of discrete data and survival data. Applications to real data will be emphasized.
Course Note: BIO 210, BIO 213, or BIO 230 required, or signature of instructor.
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.
Course Evaluations
BIO224 Survival Methods in Clinical Research
Summer 2
Dr. R. Davis
2.5 credits
Lectures. Five 2-hour sessions each week.
This course will cover the common approaches to the display and analysis of survival data, including Kaplan-Meier curves, log rank tests, and Cox proportional hazards regression. Computing, using SAS, will be an integral component of the course.
Course Note: BIO 210, BIO 211, BIO 213 or signature of instructor required. (rev. 10.06)
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.
Course Evaluations
BIO226 Applied Longitudinal Analysis
Spring
Dr. M. Hughes
5 credits
Lectures, laboratories. Two 2-hour sessions each week.
This course covers modern methods for the analysis of repeated measures, correlated outcomes and longitudinal data, including the unbalanced and incomplete data sets characteristic of biomedical research. Topics include an introduction to the analysis of correlated data, analysis of response profiles, fitting parametric curves, covariance pattern models, random effects and growth curve models, and generalized linear models for longitudinal data, including generalized estimating equations (GEE) and generalized linear mixed effects models (GLMMs).
Course Activities: Homework assignments will focus on data analysis in SAS using PROC GLM, PROC MIXED, PROC GENMOD, and PROC NLMIXED.
Course Note: BIO 210, BIO 211, BIO 213, or BIO 232, or signature of instructor required; lab or section times will be announced at first meeting.
Course Evaluations
BIO227 Fundamental Concepts in Gene Mapping
Fall 2
Dr. C. Lange.
2.5 Credits
Lectures, laboratories. Two 1.5-hour sessions each week.
This course introduces students to the diverse statistical methods used throughout the process of genetic epidemiology, from familial aggregation and segregation studies to linkage scans candidate-gene association studies. Topics covered include multipoint and model-free linkage analysis, linkage disequilibrium, family-based and population-based association test, and study design. Instructors use ongoing research into the genetics of asthma and cancer to illustrate basic principles. Homework includes analysis projects to familiarity students with state-of-the-art software for linkage analysis, family-based association tests, and case-control studies. Some familiarity with molecular biology and statistical hypothesis testing (e.g. material covered in EPI249 and BIO201) is helpful, although not necessary, as relevant concepts will be reviewed in lectures and labs. Students should leave with a basic understanding of how to read and evaluate statistical studies of genetics epidemiology.
Course Note: Lab or section time will be announced at first meeting.
Course Evaluations
BIO230 Probability Theory and Applications I
Fall
Cross listed at FAS as BIST230
Dr. A. Schwartzmen
5 credits
Lectures, laboratories. Two 2-hour sessions each week. One 2-hour lab each week.
Axiomatic foundations of probability, independence, conditional probability, joint distributions, transformations, moment generating functions, characteristic functions, moment inequalities, sampling distributions, modes of convergence and their interrelationships, laws of large numbers, central limit theorem, and stochastic processes.
Course Note: Enrollment in the Biostatistics department, or BIO 222, or signature of instructor required; lab or section times to be announced at first meeting; cross-listed: HSPH student must register for HSPH course. (5.06)
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.
Course Evaluations
BIO231 Statistical Inference I
Spring
Cross-listed as FAS as BIST231
Dr.Y. Li
5 credits
Lectures, laboratories. Two 2-hour sessions each week. One 1.5-hour lab each week.
A fundamental course in statistical inference. Discusses general principles of data reduction: exponential families, sufficiency, ancillarity and completeness. Describes general methods of point and interval parameter estimation and the small and large sample properties of estimators: method of moments, maximum likelihood, unbiased estimation, Rao-Blackwell and Lehmann-Scheffe theorems, information inequality, asymptotic relative efficiency of estimators. Describes general methods of hypothesis testing and optimality properties of tests: Neyman-Pearson theory, likelihood ratio tests, score and Wald tests, uniformly and locally most powerful tests, asymptotic relative efficiency of tests.
Course Note: BIO 230 or signature of instructor required; lab or section time to be announced at first meeting; cross-listed: HSPH student must register for HSPH course.
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.
Course Evaluations
BIO232 Methods I
Fall
Cross-listed at FAS as BIST232
Dr. V. DeGruttola
5 credits
Lectures. Two 2-hour sessions each week.
Introductory course in the analysis of Gaussian and categorical data. The general linear regression model, ANOVA, robust alternatives based on permutations, model building, resampling methods (bootstrap and jackknife), contingency tables, exact methods, logistic regression.
Course Note: Enrollment in the Department of Biostatistics, or signature of instructor required; lab or section times to be announced at first meeting; cross-listed: HSPH student must register for HSPH course. (5.06)
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.
Course Evaluations
BIO233 Methods II
Spring
Dr. B. Coull
5 credits
Lectures, laboratories (optional). Two 2-hour sessions each week. One 1.5-hour lab each week.
Intermediate course in the analysis of Gaussian, categorical, and survival data. The generalized linear model, Poisson regression, random effects and mixed models, comparing survival distributions, proportional hazards regression, splines and smoothing, the generalized additive model.
Course Note: BIO 232, or signature of instructor required; lab or section times to be announced at first meeting.
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.
Course Evaluations
BIO234 Research Synthesis & Meta-Analysis in Public Health & Medicine
Summer 2
Dr. M. Stoto
2.5 credits
Lectures. Five 2-hour sessions each week.
Concerned with the use of existing data to inform clinical decision making and health care policy, the course focuses on research synthesis (meta-analysis). The principles of meta-analytic statistical methods are reviewed and the application of these to data sets is explored. Application of methods includes considerations for clinical trials and observational studies. The use of meta-analysis to explore data and identify sources of variation among studies is emphaiszed, as is the use of meta-analysis to identify future research questions.
Course Activities: Students prepare a protocol to conduct a meta-analysis and use existing meta-analysis software to apply principles outlined in the course to data sets provided for this purpose.
Course Note: This course is equivalent to EPI233; credit will not be given for both courses. (rev. 10.03)
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.
Course Evaluations
BIO235 Regression and Analysis of Variance
Fall
Dr. M. Zelen
5 credits
Lectures, laboratories. Two 2-hour sessions each week. One 2-hour lab each week.
This is an advanced course in data analysis for linear models - regression and analysis of variance. Estimation methods (maximum likelihood and least squares) and issues of inference (confidence intervals, hypothesis testing, analysis of residuals) are presented from a theoretical and data analysis perspective. Background in matrix algebra and linear regression required.
Course Note: BIO230 and BIO232, or signature of instructor required; lab or section times to be announced at first meeting; cross-listed, HSPH student must register for HSPH course.
(5.06)
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.
Course Evaluations
BIO237 Modern Statistical Computing Environments
Fall
Dr. C. Li
5 Credits
Lectures, Laboratroies. Two 1.5-hour session each week.
Acquaints students with statistical computing enviroments under Windows and Linux systems. Taught in a computing lab, the course consists of lectures, demonstrations and hands-on exercises. Example topics include R, SAS, LaTeX, Python, and online resources.
Course Note: Enrollment in a biostatistics or related degree program required; no auditors.
Course Evaluations
BIO238 Advanced Topics in Clinical Trails
Spring 2
Dr. S. Lagakos
2.5 Credits
Lectures. Two 1.5-hour sessions each week. One 1.5-hour lab each week.
This course will focus on selected advanced topics in the design, analysis, and interpretation of clinical trials, including study design; choice of endpoints (including surrogate endpoints); interim analyses and group sequential methods; subgroup analyses; and meta-analyses.
Course note: BIO214, BIO230, and BIO231 (may be taken concurrently) or signature of instructor required.
Course Evaluations
BIO243 Nonparametric Methods
Spring 1
Dr. M. Hughes
2.5 credits
Course not offered 2005-2006; offered alternate years.
Lectures. Two 2-hour sessions each week.
Presents the theory and application of nonparametric methods. Topics include permutation tests, permutation limit theorems, 2-sample rank tests and their asymptotic efficiency, k-sample rank tests, 1-sample tests of location, paired comparisons, rank tests for symmetry and independence, and analogues of linear modeling based on ranks.
Course Note: BIO231 required.
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.
Course Evaluations
BIO244 Analysis of Failure Time Data
Fall
Dr. J. Lok
5 credits
Lectures. Two 2-hour sessions each week.
Discusses the theoretical basis of concepts and methodologies associated with survival data and censoring, nonparametric tests, and competing risk models. Much of the theory is developed using counting processes and martingale methods. Material is drawn from recent literature.
Course Note: BIO 231 and BIO 233 required; cross-listed, HSPH student must register for HSPH course (5.06)
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.
Course Evaluations
BIO245 Analysis of Multivariate and Longitudinal Data
Spring
Cross-listed at FAS as BIST245
Dr. X. Lin
5 credits
Lectures. Two 2-hour sessions each week.
Presents classical and modern approaches to the analysis of multivariate observations, repeated measures, and longitudinal data. Topics include the multivariate normal distribution, Hotelling's T2, MANOVA, the multivariate linear model, random effects and growth curve models, generalized estimating equations, statistical analysis of multivariate categorical outcomes, and estimation with missing data. Discusses computational issues for both traditional and new methodologies.
Course Note: BIO 231 and BIO 235 required; cross-listed, HSPH student must register for HSPH course. (5.06)
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.
Course Evaluations
BIO247 Design of Scientific Investigations
Spring
Cross-listed at FAS as BIST247
Dr. M. Hughes
5 credits
Course Not Offered 2008-2009; offered alternate years.
Lectures. Two 2-hour sessions and one 2-hour lab each week.
Sample size considerations, basic principles of experimental design (randomization, replication, and balance), block designs, factorial experiments, response surface modeling, optimal design, clinical trials, adaptive and sequential designs.
Course Note: BIO 235 or signature of instructor required; minimum enrollment of 10 students required; cross-listed, HSPH student must register for HSPH course. (5.06)
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.
Course Evaluations
BIO248 Advanced Statistical Computing
Spring
Dr. P. Catalano
5 credits
Not Offered 2008-2009.
Lectures. Two 2-hour sessions each week.
A course in computing algorithms useful in statistical research and advanced statistical applications. Topics include computer arithmetic, matrix algebra, numerical optimization ethods with application to maximum likelihood estimation and GEEs, spline smoothing and penalized likelihood, numerical integration, random number generation and simulation methods, Gibbs sampling, bootstrap methods, missing data problems and EM, imputation, data augmentation algorithms, and Fourier transforms. Students should be proficient with C or Fortran programming.
Course Note: BIO235, or signature of instructor required; cross-listed, HSPH student must register for HSPH course. (5.06)
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.
Course Evaluations
BIO249 Bayesian Methods in Biostatistics
Spring
Dr. C. Paciorek
5 credits
Lectures. Two 2-hour sessions each week.
General principles of the Bayesian approach, prior distributions, hierarchial models and modeling techniques, approximate inference, Markov chain Monte Carlo methods, model assessment and comparison. Bayesian approaches to GLMMs, multiple testing, nonparametrics, clinical trails, survival analysis.
BIO230 (Probability Theory and Applications I), BIO231 (Statistical Inference I), and BIO232 (Methods I), or the signature of the instructor is required. BIO233 (Methods II) will also be helpful for the second part of the course.
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.
Course Evaluations
BIO250 Probability Theory and Applications II
Spring
Dr. A. Rotnitzky
5 Credits
Not Offered 2008-2009.
Lectures. Two 2-hour sessions each week.
Basic set theory, measure theory, Riemann-Stieltjes and lebesgue integration, conditional probability, conditional expectation (projection), martingales, Randon-Nikodym derivative, product measure and Fubini's Theorem, limit theorems on sequences of random variables, stochastic processes, weak convergence.
Course Note: BIO 230 and BIO 232, or Signature of instructor required.
Course Evaluations
BIO251 Statistical Inference II
Fall
Dr. T. Cai
5 credits
Lectures. Two 2-hour sessions each week.
Sequel to BIO 231. Considers several advanced topics in statistical inference. Topics include limit theorems, multivariate delta method, properties of maximum likelihood estimators, saddlepoint approximations, asymptotic relative efficiency, robust and rank-based procedures, resampling methods, and nonparametric curve estimation.
Course Note: BIO 231 required; cross-listed, HSPH must register for HSPH course (5.06)
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.
Course Evaluations
BIO257 Advanced Statistical Genetics
Spring
Dr. C. Lange
5 credits
Lectures, laboratories. One 4-hour sessions each week. One 2-hour lab each week.
This course concentrates on the statistical aspects of genetic studies for complex-disease, covering both modern linkage and association analysis. The goal is to enable students to read fundamental papers and to engage in original research.
Course Note: BIO 231 and BIO 233, or permission of instructor required. Lab or section times to be announced at first meeting.
Course Evaluations
BIO262 Statistical Problems in Drug Development
Fall
Dr. M. Testa
2.5 credits
Course not offered 2006-2007; offered alternate years.
Lectures. One 2-hour session each week.
This course will introduce the student to the "real life" applications of statistical methodology required for pharmaceutical drug development and will feature guest lecturers from the pharmaceutical industry. Weekly seminars will cover statistical techniques used in the various phases of drug development, including assessment of pharmacologic activity; preclinical animal models and toxicology studies; clinical trials (Phase I dose ranging through Phase III comparative efficacy trials); and post-surveillance, pharmacoepidemiologic and pharmacoeconomic studies. Statistical techniques and examples include applications of optimum screening designs, use of non-parametric estimators, problems of multiplicity, tests for monotonicity, parametric and nonparametric regression, ordered categorical data analysis, survival methods, issues of power and sample size, bioequivalence studies, longitudinal data analysis, univariate and multivariate general linear models, multiple endpoint problems and quality-of-life measurement models. Exposure to
linear models and non-parametric statistics recommended.
Course Note: BIO 210, BIO 211 or BIO 213 or signature of the instructor required. (5.06)
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.
Course Evaluations
BIO263 Computational Methods for Categorical Data Analysis
Spring
Dr. C. Mehta
2.5 credits
Offered alternate years. Offered Spring 2008-2009.
Lectures. One 2-hour sessions each week.
This course deals with exact nonparametric methods of inference. These methods use fast numerical algorithms to permute the observed data in all possible ways, and thereby derive exact distributions for the test statistics of interest without making any distributional or large-sample assumptions. In contrast, standard parametric methods of inference make distributional assumptions about the data, while standard nonparametric methods of inference rely on asymptotic theory to derive approximate distributions for the test statistics. Exact nonparametric methods are particularly important for small, sparse or unbalanced data where the usual asymptotic theory breaks down. This course will cover exact inference for one, two and K-sample problems, ordered and unordered RxC contingency tables, 2x2 and 2xC contingency tables with or without stratification, and logistic regression. A unified view, encompassing both continuous and categorical data, will be presented based on the permutation principle. Modern algorithmic advances that make exact permutational inference computationally feasible will be treated in depth. The methods will be illustrated by several biomedical data sets. This course will use StatXact and LogXact statistical packages.
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.
Course Evaluations
BIO270 Statistical Science Outreach
WinterSession
Instructor TBA
2.5 credits
Course not offered 2008-2009; offered alternate years.
Seminars. Sixteen 2-hour sessions during WinterSession.
This is a seminar aimed at broadening the background of students in probability and statistics. Students will be expected to give short presentations from expository articles and papers. Articles will be chosen on the basis of ideas rather than technical content. There will be some emphasis on historical developments. This course is suitable for students in any year of the Biostatistics program.
Course Note: Enrollment in a biostatistics degree program required; this class cannot be used to satisfy the intermediate requirement for doctoral students in the Department of Biostatistics; Pass/Fail grading option only, minimum enrollment of 10 students required; signature of instructor required; Course meets 10:30 am to 12:30 pm. (5.06)
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.
Course Evaluations
BIO276 Sequential Analysis
Fall
Dr. C. Mehta
2.5 credits
Course offered 2006-2007; offered alternate years
Lectures. One 2-hour session each week.
This course will cover the basic theory underlying the design and interim monitoring of group sequential clinical trials and will illustrate the theory with examples of real clinical trials. Topics include: distribution theory for stochastic processes with independent increments; the recursive integration algorithm; stopping boundaries and error spending functions; maximum information trials; conditional power and stochastic curtailment; repeated confidence intervals; inference following group sequential testing; sample size re-estimation; more general adaptive
designs. Software support for this course will be provided by East software.
Course Note: BIO 230 or signature of instructor required. (5.06)
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.
Course Evaluations
BIO277 Computational Biology
Fall
Dr. G. Yuan
5.0 credits
Lectures. Two 2-hour sessions each week.
Instroduction to statistical methods for biological problems including microarray analysis, motif finding, CHIP-chip data, and gene regulatory network. Topics include multiple hypothesis testing, clustering and classification, variable selection, hidden Markov model, and Bayesian network.
Course Note: BIO 230 and BIO231, or permission of instructor required; ordinal grading option only. Cross-listed; HSPH students must register for HSPH course.
Course Evaluations
BIO280 Introduction to Computational Molecular Biology
Spring
Dr. X. Liu
5 credits
Course Not Offered 2007-2008.
Lectures, laboratories. Two 1.5-hour sessions each week.
Graduate entry level course to basic problems, algorithms and data analysis methods in computational biology. Topics covered in the course include sequence alignment, gene finding and annotation, microarray analysis, gene regulatory network, RNA/protein structure prediction, proteomics and pharmacogenetics. The course is targeted towards graduate students and postdocs in Biostatistics Department and Division of Biological Sciences.
Course Note: Lab or section will be announced at first meeting; cross-listed course, HSPH students must register for HSPH course.
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.
Course Evaluations
BIO283 Spatial Statistics for Health Research and Social Inquiry
Spring
Dr. C. Paciorek, Dr. L. Ryan, Dr. R. Izem
5 credits
Course Not Offered 2007-2008
Lectures, laboratories. Two 1.5-hour sessions each week. One 2-hour lab each week.
Introduction to spatial statistics with application to public health and social science research. Emphasizes methods for the analysis and visualization of three basic types of spatial data: areal data, point (geostatistical) data, and point processes. Heavy emphasis on real applied problems through case studies, guest lectures, and student projects. Basic GIS skills will be covered in a short module. Note that prerequisites are guidelines and students are encouraged to consult the instructors.
Course Note: BIO 210, or 211, or 213 and BIO 503, or permission of instructor.
Course Evaluations
BIO287 Public Health Surveillance
Spring
Dr. A. Ozonoff, Dr. M. Pagano
2.5 credits
To be given 2007-2008; offered alternate years.
Lectures. One 2-hour session each week.
Surveillance is an important component of public health. Its function is to detect and monitor disease incidence and it has three components: to collect data, to analyze it, and to report the results. This course considers all three aspects with particular emphasis on the analysis of surveillance data. We shall consider both the more traditional surveillance systems, where data collection and reporting are done at a relatively leisurely pace, and systems that provide for immediate feedback and thus are designed to detect biological terrorism and other situations where rapid response is desirable. We shall study both passive and active surveillance systems. Statistical techniques covered include time series, clustering methods, and other geo-temporal techniques.
Course Note: BIO 232, or signature of instructor required; no auditors. (9.06)
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.
Course Evaluations
BIO288 Semiparametric Methods for Analysis of Missing and Censored Data
Spring
Dr. A. Rotnitzky
2.5 credits
Course not offered 2006-2007; offered alternate years.
Lectures. One 2-hour session each week.
The goal of the course is to provide a comprehensive discussion of optimal estimation techniques for low dimensional parameters of semiparametric models (i.e. models with infinite dimensional nuisance parameters) for complex longitudinal data subject to informative censoring or missingness. The course will start with the discussion of the fundamental notions and results of semiparametric theory: pathwise derivatives, tangent space, semiparametric variance and information bounds, and influence functions. It will then provide a general estimating function methodology for locally semiparametric efficient estimation and doubly robust estimation under data that are coarsened at random. This general methodology will then be applied to derive locally efficient doubly robust estimators of 1) regression parameters in multivariate generalized linear models subject to missing at random data, 2) the survival function of an endpoint subject to dependent right censoring, 3) the quality of life adjusted survival time subject to dependent right censoring 4) the survival function of multivariate failure time data subject to univariate (dependent) censoring, 5) Cox regression parameters based on dependent right censored data and 6) smooth parameters of the distribution of a time to an endpoint outcome based on current status data and interval censored data.
Course note: BIO231, BIO244, and BIO250 or signature of instructor required. (5.06)
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.
Course Evaluations
BIO289 Reading the Medical Literature: A Course for Statisticians
WinterSession
Dr. D. Neuberg
1.25 Credits
Course not offered 2006-2007
Seminars. Eight 2-hour sessions.
The goal of this course is to offer students the opportunity to improve their skills at critical reading of the medical literature. Papers will be approached from a statistical point of view, and discussion will focus how to identify the structure of the clinical study, including the statistical design, from the ultimate published report of results. Papers will be drawn from the recent medical literature, with an emphasis on publications appearing in the New England Journal of Medicine, Lancet, and other journals of similar nature. For each paper, one student will summarize the content of the paper, and a second student will critique the paper. All students are expected to read every paper, and be prepared to participate in classroom discussion.
Course note: Registration will be limited to students enrolled in a degree program in Statistics or Biostatistics; pass/fail grading option only. (5.06)
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.
Course Evaluations
BIO291 Statistical Methods for Causality
Spring
Dr. Rotnitzky, Dr. Tchetgen, Dr. Li, Dr. Robins
5 credits
Lectures, laboratories. Two 2-hour sessions each week. One 2-hour lab each week.
Theory of directed acyclic graph models. Identifiability of causal contrasts. Theory and applications of locally semiparametric efficient doubly-robust estimation in two models for counterfactual variables: marginal structural models and structural nested models.
Course Note: BIO 231, or permission of instructor required. Lab or section times to be announced at first meeting. Minimum enrollment required.
Course Evaluations
BIO300 Independent Study
Fall 1
Department Members
Time and credit to be arranged.
An opportunity for independent study is offered for interested and qualified students or small groups of students. Arrangements must be made with individual faculty members and are limited by the amount of faculty time available. These programs are open to all students who wish to go beyond the content of the regular courses.
Course Note: Completed independent study contract is required at the time of registration; maximum of 5 credits per independent study topic; pass/fail only; signature of instructor required. (5.06)
Course Evaluations
BIO300 Independent Study
Fall
Department Members
Time and credit to be arranged.
An opportunity for independent study is offered for interested and qualified students or small groups of students. Arrangements must be made with individual faculty members and are limited by the amount of faculty time available. Theses programs are open to all students who wish to go beyond the content of regular courses.
Course Note: Completed independent study/ tutorial contract is required at the time of registration; maximum of 5 credits per independent study topic; pass/fail grading option only; signature of instructor required. (5.06)
Course Evaluations
BIO300 Independent Study/ Tutorial
Fall 2
Department Members
Time and credit to be arranged.
An opportunity for independent study is offered for interested and qualified students or small groups of students. Arrangements must be made with individual faculty members and are limited by the amount of faculty time available. Theses programs are open to all students who wish to go beyond the content of regular courses.
Course Note: Completed independent study/ tutorial contract is required at the time of registration; maximum of 5 credits per independent study topic; pass/fail grading option only; signature of instructor required. (5.06)
Course Evaluations
BIO300 Independent Study/ Tutorial
Spring 1
Department Members
Time and credit to be arranged.
An opportunity for independent study is offered for interested and qualified students or small groups of students. Arrangements must be made with individual faculty members and are limited by the amount of faculty time available. Theses programs are open to all students who wish to go beyond the content of regular courses.
Course Note: Completed independent study/ tutorial contract is required at the time of registration; maximum of 5 credits per independent study topic; pass/fail grading option only; signature of instructor required. (5.06)
Course Evaluations
BIO300 Independent Study/ Tutorial
Spring
Department Members
Time and credit to be arranged.
An opportunity for independent study is offered for interested and qualified students or small groups of students. Arrangements must be made with individual faculty members and are limited by the amount of faculty time available. Theses programs are open to all students who wish to go beyond the content of regular courses.
Course Note: Completed independent study/ tutorial contract is required at the time of registration; maximum of 5 credits per independent study topic; pass/fail grading option only; signature of instructor required. (5.06)
Course Evaluations
BIO300 Independent Study/ Tutorial
Spring 2
Department Members
Time and credit to be arranged.
An opportunity for independent study is offered for interested and qualified students or small groups of students. Arrangements must be made with individual faculty members and are limited by the amount of faculty time available. Theses programs are open to all students who wish to go beyond the content of regular courses.
Course Note: Completed independent study/ tutorial contract is required at the time of registration; maximum of 5 credits per independent study topic; pass/fail grading option only; signature of instructor required. (5.06)
Course Evaluations
BIO300 Independent Study/ Tutorial
WinterSession
Department Members
Time and credit to be arranged.
An opportunity for independent study is offered for interested and qualified students or small groups of students. Arrangements must be made with individual faculty members and are limited by the amount of faculty time available. Theses programs are open to all students who wish to go beyond the content of regular courses.
Course Note: Completed independent study/ tutorial contract is required at the time of registration; maximum of 5 credits per independent study topic; pass/fail grading option only; signature of instructor required. (5.06)
Course Evaluations
BIO300 Independent Study/ Tutorial
Summer
Department Members
Time and credit to be arranged.
Guided study in specific areas of statistical methodology and applications.
Course Note: Completed independent study contract is required at the time of registration; maximum of 5 credits per independent study topic; pass/fail only; signature of instructor required; students may register for a maximum of 5 credits in the summer term.
Course Evaluations
BIO300 Independent Study/ Tutorial
Summer 2
Department Members
Time and credit to be arranged.
Guided study in specific areas of statistical methodology and applications.
Course Note: Completed independent study contract is required at the time of registration; maximum of 5 credits per independent study topic; pass/fail only; signature of instructor required; students may register for a maximum of 5 credits in the summer term.
Course Evaluations
BIO311 Teaching
Fall 1
Dr. D. Wypij
Time and credit to be arranged.
Work with members of the department in laboratory instruction and the development of teaching materials.
Course Note: Completed independent study contract is required at the time of registration; maximum of 5 credits per independent study topic; pass/fail only; signature of instructor required. (5.06)
Course Evaluations
BIO311 Teaching
Fall
Dr. D. Wypij
Time and credit to be arranged.
Work with members of the department in laboratory instruction and the development of teaching materials.
Course Note: Completed independent study contract is required at the time of registration; maximum of 5 credits per independent study topic; pass/fail only; signature of instructor required. (5.06)
Course Evaluations
BIO311 Teaching
Fall 2
Dr. D. Wypij
Time and credit to be arranged.
Work with members of the department in laboratory instruction and the development of teaching materials.
Course Note: Completed independent study contract is required at the time of registration; maximum of 5 credits per independent study topic; pass/fail only; signature of instructor required. (5.06)
Course Evaluations
BIO311 Teaching
Spring 1
Dr. D. Wypij
Time and credit to be arranged.
Work with members of the department in laboratory instruction and the development of teaching materials.
Course Note: Completed independent study contract is required at the time of registration; maximum of 5 credits per independent study topic; pass/fail only; signature of instructor required. (5.06)
Course Evaluations
BIO311 Teaching
Spring
Dr. D. Wypij
Time and credit to be arranged.
Work with members of the department in laboratory instruction and the development of teaching materials.
Course Note: Completed independent study contract is required at the time of registration; maximum of 5 credits per independent study topic; pass/fail only; signature of instructor required. (5.06)
Course Evaluations
BIO311 Teaching
Spring 2
Dr. D. Wypij
Time and credit to be arranged.
Work with members of the department in laboratory instruction and the development of teaching materials.
Course Note: Completed independent study contract is required at the time of registration; maximum of 5 credits per independent study topic; pass/fail only; signature of instructor required. (5.06)
Course Evaluations
BIO311 Teaching
Summer 1
Dr. D. Wypij
Time and credit to be arranged.
Work with members of the department in laboratory instruction and the development of teaching materials.
Course Note: Completed independent study contract is required at the time of registration; maximum of 5 credits per independent study topic; pass/fail only; signature of instructor required; students may register for a maximum of 5 credits in the summer term.
Course Evaluations
BIO311 Teaching
Summer
Dr. D. Wypij
Time and credit to be arranged.
Work with members of the department in laboratory instruction and the development of teaching materials.
Course Note: Completed independent study contract is required at the time of registration; maximum of 5 credits per independent study topic; pass/fail only; signature of instructor required; students may register for a maximum of 5 credits in the summer term.
Course Evaluations
BIO311 Teaching
Summer 2
Dr. D. Wypij
Time and credit to be arranged.
Work with members of the department in laboratory instruction and the development of teaching materials.
Course Note: Completed independent study contract is required at the time of registration; maximum of 5 credits per independent study topic; pass/fail only; signature of instructor required; students may register for a maximum of 5 credits in the summer term.
Course Evaluations
BIO312 Consultation
Fall
Dr. D. Wypij
Time and credit to be arranged.
Work with members of the department on current statistical consultation activities.
Course Note: Completed independent study contract is required at the time of registration; maximum of 5 credits per independent study topic; pass/fail only; signature of instructor required. (5.06)
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.
Course Evaluations
BIO312 Consultation
Spring
Dr. M. Pagano
Dr. D. Wypij
Time and credit to be arranged.
Work with members of the department on current statistical consultation activities.
Course Note: Completed independent study contract is required at the time of registration; maximum of 5 credits per independent study topic; pass/fail only; signature of instructor required. (5.06)
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.
Course Evaluations
BIO312 Consultation
Summer 1
Department Members
Time and credit to be arranged.
Work with members of the department on current statistical consultation activities.
Course Note: Completed independent study contract is required at the time of registration; maximum of 5 credits per independent study topic; pass/fail only; signature of instructor required; students may register for a maximum of 5 credits in the summer term.
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.
Course Evaluations
BIO312 Consultation
Summer
Department Members
Time and credit to be arranged.
Work with members of the department on current statistical consultation activities.
Course Note: Completed independent study contract is required at the time of registration; maximum of 5 credits per independent study topic; pass/fail only; signature of instructor required; students may register for a maximum of 5 credits in the summer term.
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.
Course Evaluations
BIO312 Consultation
Summer 2
Department Members
Time and credit to be arranged.
Work with members of the department on current statistical consultation activities.
Course Note: Completed independent study contract is required at the time of registration; maximum of 5 credits per independent study topic; pass/fail only; signature of instructor required; students may register for a maximum of 5 credits in the summer term.
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.
Course Evaluations
BIO313 Computing
Fall
Dr. C. Li, Dr. D. Wypij
Time and credit to be arranged.
Course Note: Completed independent study contract is required at the time of registration; maximum of 5 credits per independent study topic; pass/fail only; signature of instructor required. (5.06)
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.
Course Evaluations
BIO313 Computing
Spring
Dr. D. Wypij
Time and credit to be arranged.
Course Note: Completed independent study contract is required at the time of registration; maximum of 5 credits per independent study topic; pass/fail only; signature of instructor required. (5.06)
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.
Course Evaluations
BIO313 Computing
Summer
Department Members
Time and credit to be arranged.
Course Note: Completed independent study contract is required at the time of registration; maximum of 5 credits per independent study topic; pass/fail only; signature of instructor required; students may register for a maximum of 5 credits in the summer term.
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.
Course Evaluations
BIO350 Research
Fall 1
Department Members
Time and credit to be arranged.
For doctoral candidates who have passed their written qualifying exam and who are undertaking advanced work along the lines of fundamental or applied research in the department.
Course Note: Pass/Fail only; maximum of 20 credits; signature of instructor required. (5.06)
Course Evaluations
BIO350 Research
Fall
Department Members
Time and credit to be arranged.
For doctoral candidates who have passed their written qualifying exam and who are undertaking advanced work along the lines of fundamental or applied research in the department.
Course Note: Pass/Fail only; maximum of 20 credits; signature of instructor required. (5.06)
Course Evaluations
BIO350 Research
Fall 2
Department Members
Time and credit to be arranged.
For doctoral candidates who have passed their written qualifying exam and who are undertaking advanced work along the lines of fundamental or applied research in the department.
Course Note: Pass/Fail only; maximum of 20 credits; signature of instructor required. (5.06)
Course Evaluations
BIO350 Research
Spring 1
Department Members
Time and credit to be arranged.
For doctoral candidates who have passed their written qualifying exam and who are undertaking advanced work along the lines of fundamental or applied research in the department.
Course Note: Pass/Fail only; maximum of 20 credits; signature of instructor required. (5.06)
Course Evaluations
BIO350 Research
Spring
Department Members
Time and credit to be arranged.
For doctoral candidates who have passed their written qualifying exam and who are undertaking advanced work along the lines of fundamental or applied research in the department.
Course Note: Pass/Fail only; maximum of 20 credits; signature of instructor required. (5.06)
Course Evaluations
BIO350 Research
Spring 2
Department Members
Time and credit to be arranged.
For doctoral candidates who have passed their written qualifying exam and who are undertaking advanced work along the lines of fundamental or applied research in the department.
Course Note: Pass/Fail only; maximum of 20 credits; signature of instructor required. (5.06)
Course Evaluations
BIO350 Research
WinterSession
Department Members
Time and credit to be arranged.
For doctoral candidates who have passed their written qualifying exam and who are undertaking advanced work along the lines of fundamental or applied research in the department.
Course Note: Pass/Fail only; maximum of 20 credits; signature of instructor required. (5.06)
Course Evaluations
BIO350 Research
Summer 1
Department Members
Time and credit to be arranged.
For doctoral candidates who have passed their written qualifying exam and who are undertaking advanced work along the lines of fundamental or applied research in the department.
Course Note: Pass/Fail only; maximum of 20 credits; signature of instructor required. (5.06)
Course Evaluations
BIO350 Research
Summer
Department Members
Time and credit to be arranged.
For doctoral candidates who have passed their written qualifying exam and who are undertaking advanced work along the lines of fundamental or applied research in the department.
Course Note: Pass/Fail only; maximum of 20 credits; signature of instructor required. (5.06)
Course Evaluations
BIO350 Research
Summer 2
Department Members
Time and credit to be arranged.
For doctoral candidates who have passed their written qualifying exam and who are undertaking advanced work along the lines of fundamental or applied research in the department.
Course Note: Pass/Fail only; maximum of 20 credits; signature of instructor required. (5.06)
Course Evaluations
BIO400 Non-Resident Research
Fall 1
Department Members
Time and credit to be arranged.
For doctoral candidates who have passed their Written Qualifying Examination and who are undertaking advanced work along the lines of fundamental or applied research in the department.
Course Note: Pass/Fail only; maximum of 20 credits; signature of instructor required.
Course Evaluations
BIO400 Non-Resident Research
Fall
Department Members
Time and credit to be arranged.
For doctoral candidates who have passed their Written Qualifying Examination and who are undertaking advanced work along the lines of fundamental or applied research in the department.
Course Note: Pass/Fail only; maximum of 20 credits; signature of instructor required.
Course Evaluations
BIO400 Non-Resident Research
Fall 2
Department Members
Time and credit to be arranged.
For doctoral candidates who have passed their Written Qualifying Examination and who are undertaking advanced work along the lines of fundamental or applied research in the department.
Course Note: Pass/Fail only; maximum of 20 credits; signature of instructor required.
Course Evaluations
BIO400 Non-Resident Research
Spring 1
Department Members
Time and credit to be arranged.
For doctoral candidates who have passed their Written Qualifying Examination and who are undertaking advanced work along the lines of fundamental or applied research in the department.
Course Note: Pass/Fail only; maximum of 20 credits; signature of instructor required.
Course Evaluations
BIO400 Non-Resident Research
Spring
Department Members
Time and credit to be arranged.
For doctoral candidates who have passed their Written Qualifying Examination and who are undertaking advanced work along the lines of fundamental or applied research in the department.
Course Note: Pass/Fail only; maximum of 20 credits; signature of instructor required.
Course Evaluations
BIO400 Non-Resident Research
Spring 2
Department Members
Time and credit to be arranged.
For doctoral candidates who have passed their Written Qualifying Examination and who are undertaking advanced work along the lines of fundamental or applied research in the department.
Course Note: Pass/Fail only; maximum of 20 credits; signature of instructor required.
Course Evaluations
BIO400 Non-Resident Research
WinterSession
Department Members
Time and credit to be arranged.
For doctoral candidates who have passed their Written Qualifying Examination and who are undertaking advanced work along the lines of fundamental or applied research in the department.
Course Note: Pass/Fail only; maximum of 20 credits; signature of instructor required.
Course Evaluations
BIO400 Non-Resident Research
Summer 1
Department Members
Time and credit to be arranged.
For doctoral candidates who have passed their Written Qualifying Examination and who are undertaking advanced work along the lines of fundamental or applied research in the department.
Course Note: Pass/Fail only; maximum of 20 credits; signature of instructor required.
Course Evaluations
BIO400 Non-Resident Research
Summer
Department Members
Time and credit to be arranged.
For doctoral candidates who have passed their Written Qualifying Examination and who are undertaking advanced work along the lines of fundamental or applied research in the department.
Course Note: Pass/Fail only; maximum of 20 credits; signature of instructor required.
Course Evaluations
BIO400 Non-Resident Research
Summer 2
Department Members
Time and credit to be arranged.
For doctoral candidates who have passed their Written Qualifying Examination and who are undertaking advanced work along the lines of fundamental or applied research in the department.
Course Note: Pass/Fail only; maximum of 20 credits; signature of instructor required.
Course Evaluations
BIO501 Linear and Longitudinal Regression
Summer 2
Dr. G. Fitzmaurice
2.5 credits
Lectures, laboratories. 5 1.75-hour sessions each week.
This course is intended for students who are already very comfortable with fundamental techniques in statistics. The course will cover methods for building and interpreting linear regression models, including statistical assumptions and diagnostics, estimation and testing, and model building techniques. These models will be extended to handle data arising from longitudinal studies employing repeated measurement of subjects over time. Lectures will be accompanied by computing exercises using the SAS statistical package.
Course Note: BIO200, or BIO201, or BIO206, or BIO202 and BIO203 is required. Ordinal grading option only. Lab or section will be announced at first meeting
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.
Course Evaluations
BIO503 Introduction to Programming and Statistical Modeling in R
WinterSession
TBA, Dr. C. Paciorek (S)
1.25 credits
Seminars. Five 3-hour sessions during WinterSession
This course is an introduction to R, a powerful and flexible statistical language and environment that also provides more flexible graphics capabilities than other popular statistical packages. The course will introduce students to the basics of using R for statistical programming, computation, graphics, and modeling. We will start with a basic introduction to the R language, reading and writing data, and graphics. We then discuss writing functions in R and tips on programming in R. Finally, the latter part of the course will focus on using R to fit some important types of statistical models, including linear regression, generalized linear models, generalized additive models, and mixed effects models.
Our goal is to get students up and running with R such that they can use R in their research and are in a good position to expand their knowledge of R on their own. Basic knowledge of statistics at the level of a basic understanding of linear regression is required.
Course note: Pass/Fail or audit grading option only.
Course Evaluations
BIO504 Introduction to Geographical Information Systems Using ArcGIS
WinterSession
TBA, Dr. C. Paciorek (S)
1.25 credits
Lectures. Five 3.5 hour sessions each week.
This course introduces Geographic Information Systems (GIS) and their applications. GIS is a combination of software and hardware with capabilities for manipulating, analyzing and displaying spatially referenced information. Emphasis on learning practical skills using ArcGIS software. Five combined lecture/lab sessions. (10.06)
Course Evaluations
BIO505 Database Design and Usage for Health Research
WinterSession
Dr. J. White, Dr. J. Quackenbush
1.25 credits
Not Offered 2008-2009
Lectures. Eight 2-hour sessions.
Essential concepts needed to design, implement, and use a database using Oracle Express. Principles of relational database structures and objects, Structured Query Language (SQL), security concepts, schema design, referential integrity, and basic database administration. Students will learn to produce reports and datasets that can be imported into a statistical analysis package. Special emphasis on studies that incorporate high dimensional genetics and genomic data.
Course Note: Ordinal grading option only.
Course Evaluations
BIO506 Introductory Genomics & Bioinformatics for Health Research
Spring 1
Dr. J. Quackenbush
2.5 Credits
Lectures. Two 2-hour sessions each week.
This survey course is intended for a wide audience and will provide an introduction to genomics-inspired techniques and bioinformatics tools, including genome sequencing, DNA microarrays, proteomics, and publicly available databases and software tools.
Course Note : BIO200, or BIO201, or BIO202 and BIO203, or BIO206 and one of BIO207, BIO208, or BIO209, and EPI200 or EPI201, or signature of instructor required; lab or section times to be announced at first meeting.
Course Evaluations
ID265 Practice of Quantitative Methods
Spring 1
Department of Biostatistics and the Master of Public Health Program
Dr. M. Testa, D. Simonson
2.5 credits
Lectures, seminars, case studies. Two 2-hour sessions each week.
Explores practical and conceptual issues in the design, conduct, analysis and evaluation of human studies through the discussion of current research and methodologies. Students design studies to address important health problems. Class discussion and group projects are emphasized.
Course Note: Acceptance into the MPH concentration in Quantitative Methods or signature of instructor required. (5.06)
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.
Course Evaluations
RDS280 Decision Analysis for Health and Medical Practices
Fall 2
Department of Health Policy and Management and the Department of Biostatistics
Dr. S. Goldie
2.5 credits
Lectures. Two 2-hour sessions each week.
This course is designed to introduce the student to the methods and growing range of applications of decision analysis and cost-effectiveness analysis in health care technology assessment, medical decision making, and health resource allocation. The objectives of the course are: (1) to provide a technical understanding of the methods used, (2) to give the student an appreciation of the practical problems in applying these methods to the evaluation of clinical interventions and public health policies, and (3) to give the student an appreciation of the uses and limitations of these methods in decision making at the individual, organizational, and policy level both in developed and developing countries.
Course Note: Introductory course in probability and statistics required; BIO200, BIO201, or BIO203 may be taken concurrently; introductory economics is recommended but not required.
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.
Course Evaluations
RDS282 Cost-Effectiveness and Cost-Benefit Analysis for Hlth Prog. Eval
Spring 2
Department of Health Policy and Management and Department of Biostatistics and Department of Population and International Health
Dr. J. Salomon, Dr. M. Weinstein,
2.5 credits
Lectures, seminars. Two 2-hour sessions each week.
Provides an introduction to methods for economic evaluation of health and environmental programs, including theory and applications. Topics include theory of benefit-cost and of cost-effectiveness analysis, definition and methods for estimating costs, stated-preference and revealed-preference methods for valuing health and mortality risk, quality adjusted life years.
Course Note: Introductory decision analysis (e.g. RDS280, HPM286) and economics (e.g. HPM205, HPM206) are recommended. (5.06)
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.
Course Evaluations
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