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 also available for: COMP, AAAD, AMST, ANTH, APPL, ASTR, BCB, BIOL, BIOS, BMME, CHEM, CLAR, CMPL, COMM, DATA, DRAM, ECON, EDUC, ENEC, ENGL, ENVR, EPID, EXSS, GEOG, HBEH, INLS, LING, MATH, MEJO, PHIL, PHYS, PLAN, PLCY, POLI, PSYC, SOCI, STOR, WGST

Data last updated: 2024-09-04 10:44:58.491120

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 | Seats filled | 24/24 | 0/999 |

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 | 22/24 | 22/24 | 0/999 |

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 | 18/45 | 18/45 | 0/999 |

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 | 51/52 | 59/60 | 0/999 |

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 | 18/45 | Seats filled | 18/45 | 0/999 |

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 | 59/60 | Seats filled | 59/60 | 0/999 |

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 | -1/0 | 44/50 | 43/50 | 0/999 |

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. | ||||||||

13206 | BIOS 540 - 043 Problems in Biostatistics | MoWeFr 8:00AM - 8:50AM | Jane Monaco | TBA | 1/5 | Seats filled | 1/5 | |

Description: Arrangements to be made 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. 1 - 15 units. | ||||||||

1149 | BIOS 600 - 001 Principles of Statistical Inference | TuTh 8:00AM - 9:15AM | Marcus Herman-Giddens | McGavran-Greenberg -Rm 1301 | Seats filled | 69/100 | 69/100 | 0/999 |

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 | 25/60 | 25/60 | 0/999 |

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 | 69/100 | Seats filled | 69/100 | 0/999 |

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 | 25/60 | Seats filled | 25/60 | 0/999 |

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 | 40/50 | 40/50 | 0/999 |

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 | 29/60 | 29/60 | 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 | 54/60 | 54/60 | 0/999 |

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 | 38/60 | 38/60 | 0/999 |

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 | -3/0 | 58/60 | 55/60 | 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 | 48/90 | Seats filled | 48/90 | 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 | 23/30 | Seats filled | 23/30 | 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 | 11/30 | Seats filled | 11/30 | 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 | 16/25 | 16/40 | 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 | 33/35 | Seats filled | 33/35 | 0/999 |

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. | ||||||||

18067 | BIOS 690 - 046 Special Topics in Biostatistics | MoWeFr 8:00AM - 8:50AM | Bryce Rowland | TBA | Seats filled | Seats filled | 3/3 | |

Description: Field/topical/research seminar. Instructors use this course to offer instruction in particular topics or approaches. 1 - 3 units. | ||||||||

1157 | BIOS 691 - 001 Field Observations in Biostatistics | Mo 2:30PM - 4:25PM | Kara McCormack | Rosenau Hall-Rm 0133 | 37/48 | Seats filled | 72/83 | 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 | 26/40 | 26/40 | 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 | 23/25 | 23/30 | 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 | 30/35 | 30/35 | 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 | 27/30 | 27/30 | 0/999 |

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, Didong Li | Hooker Research Cen-Rm 0001 | Seats filled | 71/100 | 71/100 | 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. | ||||||||

1267 | BIOS 850 - 001 Training in Statistical Teaching in the Health Sciences | MoWeFr 8:00AM - 8:50AM | Marcus Herman-Giddens, Vanessa Miller | TBA | 3/5 | Seats filled | 3/5 | 0/999 |

Description: Required preparation, 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. 1 - 21 units. | ||||||||

11508 | BIOS 850 - 013 Training in Statistical Teaching in the Health Sciences | MoWeFr 8:00AM - 8:50AM | Todd Schwartz | TBA | Seats filled | Seats filled | 1/1 | 0/999 |

Description: Required preparation, 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. 1 - 21 units. | ||||||||

11496 | BIOS 850 - 017 Training in Statistical Teaching in the Health Sciences | MoWeFr 8:00AM - 8:50AM | Jonathan Toups | TBA | 1/5 | Seats filled | 1/5 | 0/999 |

Description: Required preparation, 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. 1 - 21 units. | ||||||||

17988 | BIOS 850 - 040 Training in Statistical Teaching in the Health Sciences | MoWeFr 8:00AM - 8:50AM | HAIBO ZHOU | TBA | Seats filled | Seats filled | 1/1 | |

Description: Required preparation, 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. 1 - 21 units. | ||||||||

1566 | BIOS 850 - 043 Training in Statistical Teaching in the Health Sciences | MoWeFr 8:00AM - 8:50AM | Jane Monaco | TBA | 2/3 | Seats filled | 2/3 | 0/999 |

Description: Required preparation, 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. 1 - 21 units. | ||||||||

17974 | BIOS 850 - 046 Training in Statistical Teaching in the Health Sciences | MoWeFr 8:00AM - 8:50AM | Bryce Rowland | TBA | Seats filled | Seats filled | 1/1 | |

Description: Required preparation, 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. 1 - 21 units. | ||||||||

1910 | BIOS 850 - 062 Training in Statistical Teaching in the Health Sciences | MoWeFr 8:00AM - 8:50AM | Jane Eslinger | TBA | Seats filled | Seats filled | 2/2 | 0/999 |

Description: Required preparation, 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. 1 - 21 units. | ||||||||

17973 | BIOS 850 - 085 Training in Statistical Teaching in the Health Sciences | MoWeFr 8:00AM - 8:50AM | Kara McCormack | TBA | Seats filled | Seats filled | 1/1 | |

Description: Required preparation, 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. 1 - 21 units. | ||||||||

1266 | BIOS 850 - 090 Training in Statistical Teaching in the Health Sciences | MoWeFr 8:00AM - 8:50AM | KINH TRUONG | TBA | Seats filled | Seats filled | 1/1 | 0/999 |

Description: Required preparation, 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. 1 - 21 units. | ||||||||

1992 | BIOS 850 - 099 Training in Statistical Teaching in the Health Sciences | MoWeFr 8:00AM - 8:50AM | Charles Pepe-Ranney | TBA | Seats filled | Seats filled | 1/1 | 0/999 |

Description: Required preparation, 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. 1 - 21 units. | ||||||||

1649 | BIOS 990 - 011 Research in Biostatistics | MoWeFr 8:00AM - 8:50AM | Joseph Ibrahim | TBA | Seats filled | Seats filled | 2/2 | 0/999 |

Description: 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. 1 - 21 units. |