BIOS Courses

Here is information about BIOS class enrollment for fall 2024. Classes with no meeting time listed are not shown. Feel free to contact me with any questions/comments/issues. I am happy to add any departments that are missing from these listings, just reach out to ask!

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Data last updated: 2024-07-26 11:17:49.419431

Class Number	Class	Meeting Time	Instructor	Room	Unreserved Enrollment	Reserved Enrollment	Total Enrollment	Wait List
1356	BIOS 500H - 001 Introduction to Biostatistics	TuTh 11:00AM - 12:15PM	Jane Monaco	Rosenau Hall-Rm 0230	Seats filled	21/24	21/24	2/999
Description: Prerequisite, MATH 231 and 232; corequisite, BIOS 511. Access to SAS, Excel required. Permission of instructor for nonmajors. Introductory course in probability, data analysis, and statistical inference designed for B.S.P.H. biostatistics students. Topics include sampling, descriptive statistics, probability, confidence intervals, tests of hypotheses, chi-square distribution, 2-way tables, power, sample size, ANOVA, non-parametric tests, correlation, regression, survival analysis. 3 units.
1778	BIOS 500H - 002 Introduction to Biostatistics	TuTh 12:30PM - 1:45PM	Jane Monaco	Rosenau Hall-Rm 0230	Seats filled	19/24	19/24	1/999
Description: Prerequisite, MATH 231 and 232; corequisite, BIOS 511. Access to SAS, Excel required. Permission of instructor for nonmajors. Introductory course in probability, data analysis, and statistical inference designed for B.S.P.H. biostatistics students. Topics include sampling, descriptive statistics, probability, confidence intervals, tests of hypotheses, chi-square distribution, 2-way tables, power, sample size, ANOVA, non-parametric tests, correlation, regression, survival analysis. 3 units.
1150	BIOS 511 - 001 Introduction to Statistical Computing and Data Management	MoWe 8:00AM - 8:50AM	Jane Eslinger	McGavran-Greenberg -Rm 1304	Seats filled	8/45	8/45	5/999
Description: Required preparation, previous or concurrent course in applied statistics. Permission of instructor for nonmajors. Introduction to use of computers to process and analyze data, concepts and techniques of research data management, and use of statistical programming packages and interpretation. Focus is on use of SAS for data management and reporting. 4 units.
11266	BIOS 511 - 002 Introduction to Statistical Computing and Data Management	MoWe 9:05AM - 9:55AM	Jane Eslinger	Rosenau Hall-Rm 0228	Seats filled	Seats filled	60/60	5/999
Description: Required preparation, previous or concurrent course in applied statistics. Permission of instructor for nonmajors. Introduction to use of computers to process and analyze data, concepts and techniques of research data management, and use of statistical programming packages and interpretation. Focus is on use of SAS for data management and reporting. 4 units.
1268	BIOS 511 - 601 Introduction to Statistical Computing and Data Management	MoWe 9:05AM - 9:55AM	Jane Eslinger	McGavran-Greenberg -Rm 2308	8/45	Seats filled	8/45	5/999
Description: Required preparation, previous or concurrent course in applied statistics. Permission of instructor for nonmajors. Introduction to use of computers to process and analyze data, concepts and techniques of research data management, and use of statistical programming packages and interpretation. Focus is on use of SAS for data management and reporting. 0 units.
11268	BIOS 511 - 602 Introduction to Statistical Computing and Data Management	MoWe 10:10AM - 11:00AM	Jane Eslinger	Rosenau Hall-Rm 0228	Seats filled	Seats filled	60/60	5/999
Description: Required preparation, previous or concurrent course in applied statistics. Permission of instructor for nonmajors. Introduction to use of computers to process and analyze data, concepts and techniques of research data management, and use of statistical programming packages and interpretation. Focus is on use of SAS for data management and reporting. 0 units.
1829	BIOS 512 - 001 Data Science Basics	TuTh 11:00AM - 12:15PM	Charles Pepe-Ranney	Rosenau Hall-Rm 0235	Seats filled	24/50	24/50	30/999
Description: Students will gain proficiency with R, data wrangling, data quality control and cleaning, data visualization, exploratory data analysis, with an overall emphasis on the principles of good data science, particularly reproducible research. The course will also develop familiarity with several software tools for data science best practices, such as Git, Docker, Jupyter, Make, and Nextflow. 3 units.
1149	BIOS 600 - 001 Principles of Statistical Inference	TuTh 8:00AM - 9:15AM	Marcus Herman-Giddens	McGavran-Greenberg -Rm 1301	Seats filled	64/100	64/100	2/999
Description: Required preparation, knowledge of basic descriptive statistics. Major topics include elementary probability theory, probability distributions, estimation, tests of hypotheses, chi-squared procedures, regression, and correlation. 3 units.
13822	BIOS 600 - 002 Principles of Statistical Inference	TuTh 8:00AM - 9:15AM	Kara McCormack	Rosenau Hall-Rm 0235	Seats filled	17/60	17/60	2/999
Description: Required preparation, knowledge of basic descriptive statistics. Major topics include elementary probability theory, probability distributions, estimation, tests of hypotheses, chi-squared procedures, regression, and correlation. 3 units.
1651	BIOS 600 - 601 Principles of Statistical Inference	Tu 3:30PM - 4:45PM	Marcus Herman-Giddens	McGavran-Greenberg -Rm 1301	64/100	Seats filled	64/100	2/999
Description: Required preparation, knowledge of basic descriptive statistics. Major topics include elementary probability theory, probability distributions, estimation, tests of hypotheses, chi-squared procedures, regression, and correlation. 0 units.
13823	BIOS 600 - 602 Principles of Statistical Inference	Tu 3:30PM - 4:45PM	Kara McCormack	McGavran-Greenberg -Rm 2306	17/60	Seats filled	17/60	2/999
Description: Required preparation, knowledge of basic descriptive statistics. Major topics include elementary probability theory, probability distributions, estimation, tests of hypotheses, chi-squared procedures, regression, and correlation. 0 units.
1745	BIOS 611 - 001 Introduction to Data Science	MoWe 3:35PM - 4:50PM	Jonathan Toups	McGavran-Greenberg -Rm 2306	Seats filled	27/50	27/50	11/999
Description: Prerequisites, MATH 232 and 416, and STOR 151. Topics will include gaining proficiency with R and Python, data wrangling, data quality control and cleaning, data visualization, exploratory data analysis, and introductory applied optimization, with an overall emphasis on the principles of good data science, particularly reproducible research. Some emphasis will be given to large data settings such as genomics or claims data. The course will also develop familiarity with software tools for data science best practices, such as Git, Docker, Jupyter, and Nextflow. 4 units.
1946	BIOS 641 - 001 Quantitative Methods for Health Care Professionals I	TuTh 9:30AM - 11:30AM	Vanessa Miller	TBA	Seats filled	19/60	19/60	0/999
Description: Course is designed to meet the needs of health care professionals to appraise the design and analysis of medical and health care studies and who intend to pursue academic research careers. Covers basics of statistical inference, analysis of variance, multiple regression, categorical data analysis. Previously offered as PUBH 741. Permission of instructor. 4 units.
1151	BIOS 650 - 001 Basic Elements of Probability and Statistical Inference I	TuTh 12:30PM - 1:45PM	KINH TRUONG	Rosenau Hall-Rm 0235	Seats filled	38/60	38/60	37/999
Description: Required preparation, two semesters of calculus (such as MATH 231, 232). Fundamentals of probability; discrete and continuous distributions; functions of random variables; descriptive statistics; fundamentals of statistical inference, including estimation and hypothesis testing. 3 units.
1153	BIOS 660 - 001 Probability and Statistical Inference I	TuTh 12:30PM - 1:45PM	ANASTASIA IVANOVA	McGavran-Greenberg -Rm 2306	Seats filled	33/60	33/60	2/999
Description: Required preparation, three semesters of calculus (such as MATH 231, 232, 233). 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. 3 units.
1154	BIOS 662 - 001 Intermediate Statistical Methods	TuTh 7:30AM - 9:15AM	Bryce Rowland	McGavran-Greenberg -Rm 2306	Seats filled	44/60	44/60	0/999
Description: Pre- or corequisites, BIOS 511 and 650. Principles of study design, descriptive statistics, sampling from finite and infinite populations, inferences about location and scale. Both distribution-free and parametric approaches are considered. Gaussian, binomial, and Poisson models, one-way and two-way contingency tables. 4 units.
1155	BIOS 665 - 001 Analysis of Categorical Data	TuTh 11:00AM - 12:15PM	Gary Koch, Todd Schwartz	McGavran-Greenberg -Rm 1301	51/90	Seats filled	51/90	0/999
Description: Prerequisites, BIOS 645, 650, and 662; permission of the instructor for students lacking the prerequisites. 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. 3 units.
1273	BIOS 665 - 601 Analysis of Categorical Data	Tu 3:30PM - 4:45PM	Gary Koch, Todd Schwartz	McGavran-Greenberg -Rm 1305	14/30	Seats filled	14/30	0/999
Description: Prerequisites, BIOS 645, 650, and 662; permission of the instructor for students lacking the prerequisites. 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. 0 units.
1274	BIOS 665 - 602 Analysis of Categorical Data	We 3:35PM - 4:50PM	Gary Koch, Todd Schwartz	Hooker Research Cen-Rm 0003	24/30	Seats filled	24/30	0/999
Description: Prerequisites, BIOS 645, 650, and 662; permission of the instructor for students lacking the prerequisites. 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. 0 units.
1275	BIOS 665 - 603 Analysis of Categorical Data	Th 3:30PM - 4:45PM	Gary Koch, Todd Schwartz	Hooker Research Cen-Rm 0003	13/30	Seats filled	13/30	0/999
Description: Prerequisites, BIOS 645, 650, and 662; permission of the instructor for students lacking the prerequisites. 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. 0 units.
1156	BIOS 667 - 001 Applied Longitudinal Data Analysis	MoWe 1:25PM - 2:40PM	BAHJAT QAQISH	McGavran-Greenberg -Rm 2308	12/25	Seats filled	32/45	0/999
Description: Prerequisites, BIOS 661 and BIOS 663; permissions from the instructor for students lacking the prerequisite. Matrix-based longitudinal data analysis emphasizing applications and interpretation. Linear and generalized linear, marginal and mixed regression models. Fixed effects and random effects. Maximum likelihood, REML, GEE. Regression diagnostics. Sample size. Simulation of longitudinal data. 3 units.
1580	BIOS 672 - 001 Topics in Real Analysis, Introduction to Measure Theory	Tu 3:30PM - 4:20PM	ANASTASIA IVANOVA	Rosenau Hall-Rm 0235	0/15	10/25	10/40	0/999
Description: Corequisite, BIOS 660. Selected topics in calculus, real analysis including Taylor's series, Riemann, Stieltjes and Lebesgue integration, and complex variables. Introduction to measure theory. 1 units.
13901	BIOS 680 - 001 Introductory Survivorship Analysis	MoWe 11:15AM - 12:30PM	HAIBO ZHOU	McGavran-Greenberg -Rm 2301	Seats filled	Seats filled	35/35	3/999
Description: Prerequisite, BIOS 661; permission of the instructor for students lacking the prerequisite. 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. 3 units.
1157	BIOS 691 - 001 Field Observations in Biostatistics	Mo 2:30PM - 4:25PM	Kara McCormack	Rosenau Hall-Rm 0133	32/55	Seats filled	67/90	0/999
Description: Field visits to, and evaluation of, major nonacademic biostatistical programs in the Research Triangle area. Field fee: $25. 1 units.
1159	BIOS 760 - 001 Advanced Probability and Statistical Inference I	MoWe 9:05AM - 10:50AM	Quefeng Li	Rosenau Hall-Rm 0235	Seats filled	25/40	25/40	0/999
Description: Prerequisite, BIOS 661; permission of the instructor for students lacking the prerequisite. Measure space, sigma-field, measurable functions, integration, conditional probability, distribution functions, characteristic functions, convergence modes, SLLN, CLT, Cramer-Wold device, delta method, U-statistics, martingale central limit theorem, UMVUE, estimating function, MLE, Cramer-Rao lower bound, information bounds, LeCam's lemmas, consistency, efficiency, EM algorithm. 4 units.
1160	BIOS 762 - 001 Theory and Applications of Linear and Generalized Linear Models	Mo 11:15AM - 1:15PM	Joseph Ibrahim	McGavran-Greenberg -Rm 1305	0/5	17/25	17/30	0/999
Description: Prerequisites, BIOS 661 and 663, MATH 547, and 416 or 577; Co-requisite, BIOS 760. Linear algebra, matrix decompositions, estimability, multivariate normal distributions, quadratic forms, Gauss-Markov theorem, hypothesis testing, experimental design, general likelihood theory and asymptotics, delta method, exponential families, generalized linear models for continuous and discrete data, categorical data, nuisance parameters, over-dispersion, multivariate linear model, generalized estimating equations, and regression diagnostics. 4 units.
13902	BIOS 774 - 001 Advanced Machine Learning	TuTh 11:00AM - 12:15PM	Didong Li	McGavran-Greenberg -Rm 1305	Seats filled	Seats filled	30/30	0/999
Description: Prerequisite, BIOS 760; BIOS 762 and one of the following: BIOS 635, BIOS 735, STOR 565, STOR 767, CS 755; Instructor Consent. This advanced machine learning course, designed for PhD students in biostatistics and related fields, centers on cutting-edge tools in ML, encompassing theory, methods, and applications. It is motivated by complex biomedical data problems, offering in-depth exploration of technical details, model understanding, and the strengths and weaknesses of various approaches. The aim is to provide a comprehensive understanding of state-of-the-art ML tools for effectively analyzing and solving intricate biomedical data challenges. 3 units.
1411	BIOS 780 - 001 Theory and Methods for Survival Analysis	TuTh 9:30AM - 10:45AM	JIANWEN CAI	McGavran-Greenberg -Rm 1305	Seats filled	29/35	29/35	0/999
Description: Prerequisites, BIOS 760 and 761; permission of the instructor for students lacking the prerequisites. Counting process-martingale theory, Kaplan-Meier estimator, weighted log-rank statistics, Cox proportional hazards model, nonproportional hazards models, multivariate failure time data. 3 units.
13903	BIOS 784 - 001 Introduction to Computational Biology	MoWe 1:25PM - 2:40PM	Michael Love	McGavran-Greenberg -Rm 2306	17/20	Seats filled	17/20	0/999
Description: Prerequisites, BIOS 661 and 663; Permission of the instructor for students lacking the prerequisites. Molecular biology, sequence alignment, sequence motifs identification by Monte Carlo Bayesian approaches, dynamic programming, hidden Markov models, computational algorithms, statistical software, high-throughput sequencing data and its application in computational biology. 3 units.
13904	BIOS 791 - 001 Empirical Processes and Semiparametric Inference	MoWe 9:05AM - 10:20AM	Michael Kosorok	McGavran-Greenberg -Rm 1305	Seats filled	Seats filled	30/30	8/999
Description: Prerequisite, BIOS 761; permission of the instructor for students lacking the prerequisite. Theory and applications of empirical process methods to semiparametric estimation and inference for statistical models with both finite and infinite dimensional parameters. Topics include bootstrap, Z-estimators, M-estimators, semiparametric efficiency. 3 units.
1161	BIOS 843 - 001 Seminar in Biostatistics	Th 3:30PM - 4:30PM	Xihao Li	Hooker Research Cen-Rm 0001	Seats filled	62/100	62/100	0/999
Description: This seminar course is intended to give students exposure to cutting edge research topics and hopefully help them in their choice of a thesis topic. It also allows the student to meet and learn from major researchers in the field. 1 units.