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Three views of courses offered by faculty in Biostatistics (BIOS):
A list of textbooks for for Fall 08-09 *BSURE Program This is to announce the creation of the Biostatistics Summer Undergraduate Research and Education (BSURE) Program. BSURE will be a 10-week summer undergraduate program in the Department of Biostatistics, UNC School of Public Health, to begin Summer 2008. Please click here for more information.
A list of all courses taught by Biostatistics faculty for F '07 - S '08.
BIOS 600 Principles of Statistical Inference (3 cr) BIOS 601/602 Principles of Statistical Inference - OPT LAB
BIOS 511 Introduction to Statistical Computing
and Research Data Management (4 cr) BIOS 601/602 Introduction to Statistical Computing and Research Data Management - LAB
BIOS 550 Basic Elements of Probability and
Statistical Inference I
BIOS 660 Probability and Statistical Inference I
(3cr)
BIOS 662 Intermediate Statistical Methods (4 cr) BIOS 601 Intermediate Statistical Methods - LAB
BIOS 665 Analysis of Categorical Data (3 cr) BIOS 601 Analysis of Categorical Data - OPT LAB BIOS 602 Analysis of Categorical Data - OPT LAB BIOS 603 Analysis of Categorical Data - OPT LAB BIOS 667 Applied Longitudinal Data Analysis
BIOS 670 Demographic Techniques I (3 cr)
BIOS 691 Field Observations in Biostatistics (3 cr) BIOS 700 Research Skills in Biostatistics (1 cr)
BIOS 752 Design and Analysis of Clinical Trials (3 cr)
BIOS 758 Advanced Statistical Methods in Biometric and Public Health (4 cr) BIOS 760 Advanced Probability and Statistical Inference I (4 cr) BIOS 762 Advanced Linear Models I (4 cr) BIOS 765 Models and Methodology in Categorical Data (3 cr) BIOS 781 Statistical Methods for Human Genetics (3 cr) BIOS 843 Seminar in Biostatistics (1 cr)
BIOS 541 Quantitative Methods for Health Care
Professionals I (3 cr)
BIOS 600 Principles of Statistical Inference (3 cr) BIOS 601/604 Principles of Statistical Inference - OPT LAB BIOS 960 Principles of Statistical Inference (3 cr) - WEB -BASED BIOS 545 Principles of Experimental Analysis (3 cr) BIOS 661 Probability and Statistical Inference II (3 cr) BIOS 663 Intermediate Linear Models (4 cr) BIOS 601 Intermediate Linear Models Lab BIOS 664 Sample Survey Methodolgy (4 cr) BIOS 668 Design of Public Health Studies (3 cr) BIOS 680 Introductory Survivorship Analysis (3 cr) BIOS 756 Advanced Nonparametric Methods in Biometric Research (3 cr) BIOS 763 Generalized Linear Model Theory & Applications (4 cr) BIOS 767 Longitudinal Data Analysis (4 cr) BIOS 771 Demographic Techniques (3 cr) BIOS 783 Theory and Methods of Survival Analysis (3 cr) BIOS 791 Empirical Processes and Semiparametric Inference (3 cr) BIOS 841 Principles of Statistical Consulting (3 cr) BIOS 542 Quantitative Methods for Health Care Professional II (3 cr) The following courses require special arrangements with instructor for both all semesters offered: BIOS 397, 399, 540, 541, 542, 842,850, 992, 993 and 994
These are the official
descriptions taken from the University catalog.
Additional courses may be added on a semester basis at the discretion of the
department.
BIOSTATISTICS COURSES
600 PRINCIPLES OF STATISTICAL INFERENCE (3). Prerequisite, knowledge of basic descriptive statistics. Major topics include elementary probability theory, probability distributions, estimation, tests of hypotheses, chi-squared procedures, regression, and correlation. Fall and spring. Hamer, Monaco, Bowling
511 INTRODUCTION TO STATISTICAL COMPUTING AND DATA MANAGEMENT (4). Prerequisite, previous or concurrent course in applied statistics or permission of the instructor. Introduction to use of computers to process and analyze data, components of digital computers, characteristics of magnetic storage devices, use of JCL and utility programs, concepts and techniques of research data management, use of statistical program packages and interpretation. Fall. Roggenkamp
540 ROBLEMS IN BIOSTATISTICS (1 or more). Prerequisites to be arranged with the faculty in each case. A course for students of public health who wish to make a study of some special problem in the statistics of the life sciences and public health. Fall, spring, and summer.
541 QUANTITATIVE METHODS FOR HEALTH CARE PROFESSIONALS I (3). Prerequisite, permission of instructor. Course is designed to meet the needs of health care professionals who need to be able to critically appraise the design and analysis of medical and health care studies and intend to pursue academic research careers. Basics of statistical inference, analysis of variance, multiple regression, categorical data analysis, and an introduction to logistic regression and survival analysis. Emphasis is on applied data analysis of major health care studies. Fall. Garrett
542 QUANTITATIVE METHODS FOR HEALTH CARE PROFESSIONALS II (3). Prerequisites, BIOS 541 and permission of instructor. Continuation of BIOS 541; main emphasis is on logistic regression; other topics include exploratory data analysis and survival analysis. Spring. Garrett
545 PRINCIPLES OF EXPERIMENTAL ANALYSIS (3). Prerequisites, BIOS 600 or equivalent; a basic familiarity with a statistical software package (preferably SAS) that has the capacity to do multiple linear regression analysis; permission of the instructor except for majors in School of Public Health. Continuation of Biostatistics 110; the analysis of experimental and observational data, including multiple regression, and analysis of variance and covariance. Spring. Truong
550 BASIC ELEMENTS OF PROBABILITY AND STATISTICAL INFERENCE I (GNET 150) (4). Prerequisite, MATH 232 or equivalent. Fundamentals of probability, discrete and continuous distributions; functions of random variables; descriptive statistics; fundamentals of statistical inference, including estimation and hypothesis testing. Fall. Salama
660 PROBABILITY AND STATISTICAL INFERENCE I (3). Prerequisite, MATH 233 or equivalent. Introduction to probability; discrete and continuous random variables; expectation theory; bivariate and multivariate distribution theory; regression and correlation; linear functions of random variables; theory of sampling; introduction to estimation and hypothesis testing. Fall. Kupper
661 PROBABILITY AND STATISTICAL INFERENCE II (3). Prerequisite, BIOS 660. Distribution of functions of random variables; Helmert transformation theory; central limit theorem and other asymptotic theory; estimation theory; maximum likelihood methods; hypothesis testing; power; Neyman-Pearson Theorem, likelihood ratio, score, and Wald tests; noncentral distributions. Spring. Qaqish
662 INTERMEDIATE STATISTICAL METHODS (4). Corequisites, BIOS 511, 550, or equivalents. Principles of study design, descriptive statistics, and sampling from finite and infinite populations, with particular attention to inferences about location and scale for one, two, or k sample situations. Both distribution-free and parametric approaches are considered. Gaussian, binomial, and Poisson models, one-way and two-way contingency tables, as well as related measures of association, are treated. Fall. Hudgens
663 INTERMEDIATE LINEAR MODELS (4). Prerequisite, BIOS 662 or equivalent. Matrix-based treatment of regression, one-way and two-way ANOVA, and ANCOVA, emphasizing the general linear model and hypothesis, as well as diagnostics and model building. The course begins with a review of matrix algebra, and it concludes with some treatment of statistical power for the linear model and with binary response regression methods. Spring. Truong
664 SAMPLE SURVEY METHODOLOGY (STAT 104) (4). Prerequisite, BIOS 550 or equivalent or permission of the instructor. Fundamental principles and methods of sampling populations, with primary attention given to simple random sampling, stratified sampling, and cluster sampling. Also, the calculation of sample weights, dealing with sources of nonsampling error, and analysis of data from complex sample designs are covered. Practical experience in sampling is provided by student participation in the design, execution, and analysis of a sampling project. Spring. Kalsbeek
665 ANALYSIS OF CATEGORICAL DATA (3). Prerequisites, BIOS 545, 550, and 662, or permission of the instructor. Introduction to the analysis of categorized data: rates, ratios, and proportions; relative risk and odds ratio; Cochran-Mantel-Haenszel procedure; survivorship and life table methods; linear models for categorical data. Applications in demography, epidemiology, and medicine. Fall. Koch and Schwartz
666 APPLIED MULTIVARIATE ANALYSIS (STAT 160) (3). Prerequisite, BIOS 663 or equivalent. Application of multivariate techniques, with emphasis on the use of computer programs. Multivariate analysis of variance, multivariate multiple regression, weighted least squares, principal component analysis, canonical correlation and related techniques. Not offered 2007-08.
667 APPLIED STOCHASTIC PROCESSES (3). Prerequisite, BIOS 661 or equivalent. Markov chains, Poisson processes and extensions, epidemic models, branching processes and other stochastic models of empirical processes. Disease, population, and other biostatistical applications. Not offered 2007-08.
668 DESIGN OF PUBLIC HEALTH STUDIES (3). Prerequisites, BIOS 545, 550, or equivalents. Statistical concepts in basic public health study designs: cross-sectional, case-control, prospective, and experimental (including clinical trials). Validity, measurement of response, sample size determination, matching and random allocation methods. Spring. Lavange, Catellier, Couper.
670 DEMOGRAPHIC TECHNIQUES I (3). Source and interpretation of demographic data; rates and ratios, standardization, complete and abridged life tables; estimation and projection of fertility, mortality, migration, and population composition. Fall. Suchindran, Bilsborrow.
680 INTRODUCTORY SURVIVORSHIP ANALYSIS (3). Prerequisite, BIOS 661 or permission of the instructor. Introduction to concepts and techniques used in the analysis of time to event data, including censoring, hazard rates, estimation of survival curves, regression techniques, applications to clinical trials. Spring. Zhou
691 FIELD OBSERVATIONS IN BIOSTATISTICS (1). Field visits to, and evaluation of, major nonacademic biostatistical programs in the Research Triangle area. (Field fee $25.). Fall Monaco 700 RESEARCH SKILLS IN BIOSTATISTICS (1). Prerequisites, either (1) completion of the BIOS doctoral core: BIOS 760/761 (or 758), 762, 763, and 767; or (2) passing grade on theory and applied doctoral qualifying exam in biostatistics. Fall Hering
735 STATISTICAL COMPUTING - BASIC PRINCIPLES AND APPLICATIONS (3). Prerequisites, BIOS 661; familiarity with at least one computer system and with either a computer language (C, FORTRAN, etc.) or a computer package (SAS, SPSS, etc.). Basic theory and application of computing as a tool in statistical research and practice. Topics include: algorithms and data structures, linear and nonlinear systems, function approximation, numerical integration, the EM algorithm, simulation, and document preparation. Not offered 2007-08.
BIOS 752. (3) DESIGN AND ANALYSIS OF CLINICAL TRIALS Description: This course will introduce the methods used in clinical. Topics include dose-finding trials, allocation to treatments in randomized trials, sample size calculation, interim monitoring, and non-inferiority trials. Fall. Ivanova, LaVange 756 INTRODUCTION TO NONPARAMETRIC STATISTICS (STAT 171) (3). Prerequisite, Biostatistics 661 or equivalent. Theory and application of nonparametric methods for various problems in statistical analysis. Includes procedures based on randomization, ranks, and U-statistics. A knowledge of elementary computer programming is assumed. Spring. Sen.
759 APPLIED TIME SERIES ANALYSIS (3). Prerequisites, BIOS 661 and 663 or equivalents, and permission of the instructor. Topics include correlograms, periodograms, fast Fourier transforms, power spectra, cross-spectra, coherences, ARMA and transfer-function models, spectral-domain regression. Real and simulated data sets are discussed and analyzed using popular computer software packages. Not offered 2007-08. 760 ADVANCED PROBABILITY AND STATISTICAL INFERENCE I (4). Prerequisite, BIOS 661 or permission of the instructor. Measure space, sigma-field, Lebesgue measure, measureable functions, integration, Fubini-Tonelli theorem, Radon-Nikodym theorem, probability measure, conditional probability, independence, distribution functions, characteristic functions, exponential families, convergence almost surely, convergence in probability, convergence in distribution, Borel-Cantelli leema, strong law of large numbers, central limit theorem, the Cramer-Wold device, delta method, U-statistics, martingale central limit theorem. Least squares estimation, uniformly minimal variance and unbiased estimation, estimating functions, maximum likelihood estimation, Cramer-Rao lower bound, information bounds, LeCam’s lemmas, consistency, asymptotic efficiency, expectation-maximization algorithm, nonparametric maximum likelihood estimation. Fall. Zeng. 761 ADVANCED PROBABILITY AND STATISTICAL INFERENCE II (4). Prerequisite, BIOS 760 or permission of the instructor. Description: Elementary decision theory, utility, admissibility, minimax rules, loss functions, Bayesian decision theory, likelihood ratio, Wald, and score tests, Neyman-Pearson tests, UMP and unbiased tests, rank tests, contiguity theory, confidence sets, parametric and nonparametric bootstrap methods, jackknife and cross-validation, asymptotic properties of resampling methods. Elements of Stochastic processes, including Poisson process, renewal theory, discrete-time Markov chains, continuous-time Markov chains, Martingales, and Brownian motion. Spring. Ibrahim 762 ADVANCED LINEAR MODELS I (4). Prerequisites, BIOS 661 and 663, MATH 547, MATH 416 or 577. Theory and methods for continuous responses. Topics include matrix theory, the multivariate normal distribution, multivariate quadratic forms, estimability, reparameterization, linear restrictions and splines, estimation theory, weighted least squares, multivariate tests of linear hypotheses, multiple comparisons, confidence regions, prediction intervals, statistical power, mixed models, transformations and diagnostics, growth curve models, dose-response models, missing data. Fall. Cai 763 GENERALIZED LINEAR MODEL THEORY AND APPLICATIONS (4). Prerequisite, permission of instructor if non-Bios major. Introduction to the theory and applications of generalized linear models, quasi-likelihoods, and generalized estimating equations. Topics include logistic regression, over-dispersion, Poisson regression, log-linear models, conditional likelihoods, multivariate regression models, generalized mixed models, and regression diagnostics. Spring. Zhu 764 ADVANCED SURVEY SAMPLING METHODS (3). Prerequisite, BIOS 664 or equivalent. Continuation of Biostatistics 664 for advanced students: stratification, special designs, multistage sampling, cost studies, nonsampling errors, complex survey designs, employing auxiliary information, and other miscellaneous topics. Fall. Kalsbeek 765 MODELS AND METHODOLOGY IN CATEGORICAL DATA (3). Prerequisites, BIOS 661, 663, 665, and 666 or equivalents. Theory of statistical methods for analyzing categorical data by means of linear models; multifactor and multiresponse situations; interpretation of interactions. Fall Preisser. 767 LONGITUDINAL DATA ANALYSIS (4). Prerequisite, BIOS 762. Presents modern approaches to the analysis of longitudinal data. Topics include linear mixed effects models, generalized linear models for correlated data (including generalized estimating equations), computational issues and methods for fitting models, and dropout or other missing data. Spring. Herring 771 DEMOGRAPHIC TECHNIQUES II (3). Prerequisites, BIOS 670 and integral calculus. Life table techniques; methods of analysis when data are deficient; population projection methods; interrelations among demographic variables; migration analysis; uses of population models. Spring. Suchindran 777 MATHEMATICAL MODELS IN DEMOGRAPHY (3). Prerequisite, permission of the instructor. A detailed presentation of natality models, including necessary mathematical methods, and applications; deterministic and stochastic models for population growth, migration. Not offered 2007-08. 779 BAYESIAN STATISTICS (4). Prerequisite, Biostatistics 262 or equivalent. Description: This course examines basic aspects of the Bayesian paradigm including Bayes' theorem, the likelihood principle, prior distributions, posterior distributions, and predictive distributions. General topics include Bayesian analysis of linear models, generalized linear models, random effects models, spatial models, and survival models. Additional topics include informative prior elicitation, model comparisons, Bayesian diagnostic methods, and variable subset selection. Markov chain Monte Carlo methods for computations are discussed in detail. Bayesian methods for the design and analysis of clinical trials will be examined. Fall. Ibrahim 780 THEORY AND METHODS FOR SURVIVAL ANALYSIS (3). Prerequisites, BIOS 760 and 761 or permission of the instructor. Counting process-martingale theory, Kaplan-Meier estimator, weighted log-rank statistics, Cox proportional hazards model, nonproportional hazards models, multivariate failure time data. Not offered 2007-08. 781 STATISTICAL METHODS IN HUMAN GENETICS (GNET 281) (3). Prerequisites, BIOS 661 and 663 or permission of the instructor. An introduction to statistical procedures in human genetics, Hardy-Weinberg equilibrium, linkage analysis (including use of genetic software packages), linkage disequilibrium and allelic association. Not offered 2007-08. 783 STATISTICAL METHODS IN QUANTITATIVE GENETICS (3). Prerequisites, BIOS 661 and 663 or permission of the instructor. An introduction to the statistical basis of variation in quantitative traits, with focus on experimental crosses and decomposition of trait variation, linkage map construction, statistical methodologies and computer software for mapping quantitative trait loci. Issues involving whole-genome analysis will be highlighted. Spring. Zou
791
EMPIRICAL PROCESSES AND SEMIPARAMETRIC INFERENCE (3). Prerequisites: BIOS 761 or consent of
instructor. Description: Theory and applications of empirical process methods
to semiparametric estimation and inference for statistical models with both
finite and infinite dimensional parameters. Topics include the bootstrap,
Z-estimators, M-estimators, semiparametric efficiency. credit hours: Spring.
Kosorok.
841 PRINCIPLES OF STATISTICAL CONSULTING (3). Prerequisites, BIOS 545 or equivalent and permission of the instructor except for majors in the department. An introduction to the statistical consulting process, emphasizing its nontechnical aspects. Spring. Bangdiwala and LaVange 842 PRACTICE IN STATISTICAL CONSULTING (1-3). Prerequisites, BIOS 511, 545, 550, 841, or equivalents, and permission of the instructor. Under supervision of a faculty member, the student interacts with research workers in the health sciences, learning to abstract the statistical aspects of substantive problems, to provide appropriate technical assistance, and to communicate statistical results. Fall, spring, and summer. 843 SEMINAR IN BIOSTATISICS (1). Fall and Spring. Staff. 850 TRAINING IN STATISTICAL TEACHING IN THE HEALTH SCIENCES (2 or more). Prerequisite, a minimum of one year of graduate work in statistics. Principles of statistical pedagogy. Students assist with teaching elementary statistics to students in the health sciences. Students work under the supervision of the faculty, with whom they have regular discussions of methods, content, and evaluation of performance. Fall, spring, and summer.
889 RESEARCH SEMINAR IN BIOSTATISTICS (1-3). Prerequisite, permission of the instructor. Seminar on new research developments in selected biostatistical topics. Fall and spring.
990 RESEARCH IN BIOSTATISTICS (2 or more). Individual arrangements may be made by the advanced student to spend part or all of his or her time in supervised investigation of selected problems in statistics. Fall, spring, and summer.
992 MASTER'S PAPER (3 or more). Fall, spring, and summer.
993 MASTER'S THESIS ( 3 or more). Fall, spring, and summer.
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| Last updated July 17, 2008 |
