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Biostatistics & Informatics


Colorado School of Public Health Course Book | Department of Biostatistics

BIOS 6601 Applied Biostatistics I
3.0 cr.

(Summer, Fall)

Applied biostatistical methods including descriptive and statistical inference; odds ratio and relative risk, probability theory, parameter estimation, tests for comparing statistics of two or more groups, correlation and linear regression and overviews of: multiple and logistic regression and survival analysis.

BIOS 6602 Applied Biostatistics II
3.0 cr.

(Spring) Prereq: BIOS 6601

A continuation of BIOS 6601 extending the basic principles of descriptive and inferential statistics to modeling more complex relationships using linear regression, logistic regression, and Cox regression. The statistical package SAS is used extensively.

BIOS 6603 Statistical Computing - SAS
1.0 cr.

(Spring, Summer, Fall) Prereq/Coreq: BIOS 6601 or equivalent. Restriction: Credit may be counted toward a CSPH degree for only one of BIOS 6603, 6604 or 6605.

This course will emphasize statistical analysis and data interpretation through use of the SAS statistical computing package. Instruction will be provided through laboratory exercises and interactive demonstrations.

BIOS 6604 Statistical Computing - SPSS
1.0 cr.

(Spring, Summer, Fall) Prereq/Coreq: BIOS 6601 or equivalent. Restriction: Credit may be counted toward a CSPH degree for only one of BIOS 6603, 6604 or 6605.

This course will emphasize statistical analysis and data interpretation through use of the SPSS statistical computing package. Instruction will be provided through laboratory exercises and interactive demonstrations.

BIOS 6605 Statistical Computing - R
1.0 cr.

(Spring, Summer, Fall) Prereq/Coreq: BIOS 6601 or equivalent. Restriction: Credit may be counted toward a CSPH degree for only one of BIOS 6603, 6604 or 6605.

This course will emphasize statistical analysis and data interpretation through use of the R statistical computing package. Instruction will be provided through laboratory exercises and interactive demonstrations.

BIOS 6606 Statistics for the Basic Sciences
3.0 cr.

(Fall) Restrictions: Enrollment in UCD-AMC graduate program or permission of the instructor.

This course is designed for those wishing to obtain a basic understanding of statistics and its applications in biological research. Students will develop statistical literacy and an ability to perform basic statistical analyses, basic graphical statistics, data summarizations, and estimation and inference using statistical software.

BIOS 6611 Biostatistical Methods I
3.0 cr.

(Fall) Prereq: Differential calculus or permission of instructor

This first course in applied statistics covers basic descriptive methods and probability; parametric and nonparametric inference for the one- and two-sample location problem; ANOVA, ANCOVA, and multiple linear regression. Matrix notation, R and SAS are used.

BIOS 6612 Biostatistical Methods II
3.0 cr.

(Spring) Prereq: BIOS 6611

This is a continuation of BIOS 6611, covering univariate linear modeling and emphasizing multiple regression and analysis of variance. Logistic regression and methods for correlated data are also covered. Matrix algebra and the statistical package SAS will be used.

BIOS 6621 Statistical Consulting I
1.0 cr.

(Fall) Coreq: BIOS 6611 and consent of instructor/program director.

Students will gain experience with statistical consulting and common statistical problems and techniques encountered in consulting through a combination of real examples and consultations with investigators. Emphasis will be on methods for effective consulting and communication with investigators.

BIOS 6622 Statistical Consulting II
1.0 cr.

(Spring) Prereq: BIOS 6611; Coreq: BIOS 6612 and consent of instructor/program director.

Students will gain experience with statistical consulting and common statistical problems and techniques encountered in consulting through a combination of real examples and consultations with investigators. Emphasis will be on analytic methods, and on interpretation and presentation of analyses.

BIOS 6623 Advanced Data Analysis
3.0 cr.

(Fall) Prereq: BIOS 6601 and BIOS 6602 or BIOS 6611 and BIOS 6612 or permission of instructor.

This course teaches the students how to be effective collaborators. Students will learn to modify project hypotheses to be statistical hypotheses. The students will identify and perform the appropriate data analyses and communicate their analyses both verbally and in writing.

BIOS 6628 Latent Variable Methods
3.0 cr.

(Fall) Prereq: BIOS 6601 and 6602 or equivalent. Cross-listed: CBHS 7010

Covers statistical approaches commonly used in behavioral sciences research, including reliability analysis, exploratory and confirmatory factor analysis, path analysis, structural equation modeling, and advance modeling procedures. Students will analyze data using statistical software, interpret results, and write summaries of findings.

BIOS 6629 Applied Survival and Longitudinal Data Analysis
3.0 cr.

(Fall) Prereq: BIOS 6601 and 6602 or BIOS 6611 and 6612 and permission of instructor. Restrictions: Offered in even years.

This course will focus on the application of regression modeling to time-to-event and longitudinal data. Descriptive and inferential methods will be developed for each type of data with an emphasis on graphical inspection at all stages of analysis.

BIOS 6631 Statistical Theory I
3.0 cr.

(Fall) Prereq: Differential and integral calculus

This course presents an introductory coverage of the theory of discrete and continuous random variables and applications to statistical problems. Topics include probability theory, transformations and expectations, common families of distributions, multiple random variables, and properties of a random sample.

BIOS 6632 Statistical Theory II
3.0 cr.

(Spring) Prereq: BIOS 6631 and differential and integral calculus

This course covers theoretical and applied fundamentals of statistical inference. The course is a continuation of BIOS 6631. The primary topics include point estimation, hypothesis testing, interval estimation and asymptotic methods.

BIOS 6640 Python and R in Data Science
3.0 cr.

(Spring, Fall) Pre/Coreq: BIOS 6612 or permission of instructor. Restrictions: Offered variable terms and years.

Statistical programming in Python and R, including data managing, vectors, matrices, frames, subscripting, loops, functions, input/output, packages, etc. Concepts and methods for reproducible research will be covered as well as computationally intensive statistical methods. These methods are used to analyze data and present results.

BIOS 6641 Causal Analytics in Public Health
3.0 cr.

(Spring, Fall) Pre/Coreq: BIOS 6611 or BIOS 6602 and permission of instructor; knowledge of R. Restrictions: Offered variable terms and years.

Introduction to causal inference models and machine learning; causal diagrams, propensity scores, matching, covariate balance and special topics.

BIOS 6643 Analysis of Longitudinal Data
3.0 cr.

(Fall) Prereq: BIOS 6632 and BIOS 6612 or permission of instructor

Theory and application of models appropriate for clustered and longitudinal data are studied. Models for different types of outcome variables (e.g., normal, Poisson, binomial) are covered, with an emphasis on linear mixed models for normal outcomes.

BIOS 6646 Survival Analysis
3.0 cr.

(Spring) Pre/Coreq: BIOS 6612 and BIOS 6632 or instructor permission. Restrictions: Offered in even years.

This course covers the analysis of time-to-event data with applications to biology, medicine, and public health. Nonparametric methods for group comparisons and semi-parametric regression models will be emphasized. Parametric methods and distribution theory for survival analysis will also be included.

BIOS 6648 Design and Conduct of Clinical Research
3.0 cr.

(Fall) Prereq: BIOS 6601 or BIOS 6611 or instructor permission. Restrictions: Offered in odd years.

Design and conduct of clinical research studies. Intended for non-biostatistics students. Topics include specifying the research question, study endpoints, study populations, study interventions, sample size evaluation, and choice of comparison groups. Common study designs and methods for study conduct are described.

BIOS 6649 Clinical Trials: Statistical Design and Monitoring
3.0 cr.

(Spring) Pre/Coreq: BIOS 6612 or instructor permission. Restrictions: Offered in odd years.

Statistical and scientific design of clinical trials. Intended for biostatistics graduate students. Topics include scientific and statistical aspects of the research question, endpoints, treatments, sample size evaluation. A wide range of trial designs including group sequential and adaptive trial designs are covered.

BIOS 6650 MPH Research Paper
1.0-2.0 cr.

(Spring, Summer, Fall) Prereq: Permission of department required

Independent research project resulting in a publishable paper. All projects will involve the analysis of primary or secondary data.

BIOS 6651 BIOS MS Research Paper
1.0-6.0 cr.

(Spring, Summer, Fall)

Masters research paper in Biostatistics is completed under this course.

BIOS 6655 Statistical Methods in Genetic Association Studies
3.0 cr.

(Fall) Prereq: BIOS 6612 or permission of instructor. Restrictions: Offered in variable years.

This course is designed to give an introduction to statistical methods in genetic association studies. Topics include an introduction to population genetics topics relevant to genetic association studies, design strategies, and analysis methods for case-control and family data.

BIOS 6660 Analysis of Genomics Data using R and Bioconductor
3.0 cr.

(Spring) Prereq/Coreq: BIOS 6602 or BIOS 6612, or consent of instructor. Restrictions: Offered variable terms and years

This course provides students with hands on experience in solving real life biological problems using the statistical software R and Bioconductor. Students will work and communicate with participating researchers and clinicians on their case studies of genomics data.

BIOS 6670 Special Topics: Biostatistics
1.0-3.0 cr.

(Spring, Summer, Fall)

Special interest areas of current biostatistics research and practice are presented and analyzed. The course format is lecture and discussion or seminar. Check with CSPH website for offerings and topics for this course each semester.

BIOS 6680 Data Management Using SAS
3.0 cr.

(Fall) Students will learn how to use SAS software for data management to prepare data for analyses. Main topics include importing and exporting data, variable and dataset manipulations. Introductions to producing reports, basic statistics, figures and SAS macros are also covered.

BIOS 6685 Introduction to Public Health Informatics
3.0 cr.

(Spring) Survey course explores public health informatics topics such as current public health informatics initiatives, data sources, public health information systems, standards, health information exchange, system development/procurement, threats to information security and privacy, and decision support in the public health context.

BIOS 6840 Independent Study for MPH in Biostatistics
1.0-3.0 cr.

(Spring, Summer, Fall) Course Restrictions: Open only to MPH students; Department consent required

Faculty directed independent study for MPH students in topics related to biostatistics.

BIOS 6841 Independent Study for MS in Biostatistics
1.0-3.0 cr.

(Spring, Summer, Fall) Course Restrictions: Open only to MS students or permission of instructor.

Resources of the program are available to those MS students who elect to carry out research in chosen topics related to biostatistics. A faculty member will provide guidance throughout the project.

BIOS 6950 Masters Thesis: Biostatistics
1.0-6.0 cr.

(Spring, Summer, Fall) >Biostatistics Master thesis work is completed under this course.

BIOS 7659 Statistical Methods in Genomics
3.0 cr.

(Fall, Spring) Prereq: BIOS 6611/6612 or BIOS 6631/6632 or permission of instructor; Restrictions: Offered in variable terms and variable years.

Analysis of genomic data is an integral component of biomedical research. This course will give an introduction to problems in genomics and review both the pioneering and more recent statistical methods developed for analyzing expression data and molecular sequences.

BIOS 7670 Advanced Special Topics - Biostatistics
1.0-3.0 cr.

(Spring, Summer, Fall) Advanced special interest areas of current biostatistics research and practice are presented. The course format is lecture and discussion or seminar. Check the CSPH Website for offerings and topics for this course each semester.

BIOS 7712 Statistical Methods for Correlated Data
1.0 cr.

(Spring) Prereq: BIOS 6643. Restrictions: offered variable years.

This course will cover statistical models and methods for serially correlated data, including autoregressive models, Markov models, and Markov chain Monte Carlo methods.

BIOS 7713 Statistical Methods for Missing Data
2.0 cr.

(Spring) Prereq: BIOS 6643. Restrictions: offered variable years.

This course covers methodological research being carried out for longitudinal studies with missing data. Topics include missing data mechanisms, non- ignorable missing data, multiple imputation, mixture models and sample size determinations. Students complete a project applying methods to real datasets.

BIOS 7714 Advanced Statistical Computing
3.0 cr.

(Spring, Fall) Prereq: BIOS 6612 and BIOS 6632, or permission of instructor. This course is intended for students in the Biostatistics PhD program. Restrictions: offered variable terms and years.

This course covers the theory & implementation of estimation algorithms used in statistical analysis. Possible topics: numerical analysis (quadrature), optimization (Newton0Raphson, EM algorithm, stochastic optimization), and simulation (pseudo-random numbers, rejection sampling, Markov chain methods).

BIOS 7715 Stochastic Modeling
2.0 cr.

(Spring) Prereq: BIOS 6643 and BIOS 6632 or permission of instructor. This course is intended for Biostatistics PhD students. Restrictions: offered variable years.

This course covers theory, application and software for stochastic models commonly used in health sciences, including time to event, recurrent event, multi-type recurrent event, and multi-state models.

BIOS 7716 Topics in Statistical Genetics
1.0 cr.

(Spring) Prereq: BIOS 6632 or permission of instructor. This course is intended for Biostatistics PhD students. Restrictions: offered variable years.

This course covers theory of causal models and inference as applied in Statistical Genetics. Specific methods include counterfactuals, Directed Acyclic Graph (DAG), d-separated, G-computation, marginal structural models.

BIOS 7717 Bayesian Biostatistical Methods
3.0 cr.

(Spring, Fall) Prereq: BIOS 6612 and BIOS 6632 or permission of instructor. Restrictions: Instructor consent required. Offered variable term and year.

This course will introduce students to modern Bayesian statistical modeling and inference. Topics include a comparison of frequentist and Bayesian approaches, Markov Chain Monte Carlo (MCMC) methods for simulating posterior distributions, inference for regression, hierarchical models and mixed models.

BIOS 7731 Advanced Mathematical Statistics I
3.0 cr.

(Fall) Prereq: BIOS 6632 or equivalent. This course is intended for Biostatistics PhD students. Restrictions: offered in odd years.

This course will provide the framework for understanding the formal concepts, models and assumptions in statistical theory. Topics include random variables, parameter estimation, measures of performance, hypothesis testing and asymptotic approximations.

BIOS 7732 Advanced Mathematical Statistics II
3.0 cr.

(Spring) Prereq: BIOS 7731 or equivalent. This course is intended for Biostatistics PhD students. Restrictions: offered in even years.

The foundations of the theory of point estimation. A basic introduction to measure-theoretic probability, integration, and convergence. Large sample theory, interval estimation, and efficient likelihood estimation.

BIOS 7899 Independent Study for PhD-Biostatistics
1.0-4.0 cr.

(Spring, Summer, Fall) Prereq: PhD student or permission of instructor

This course is for the PhD student who wishes to pursue one or more topics in depth. These topics may involved biostatistical material, or biological material necessary to the student's biostatistical work. Supervision by a full-time faculty member is necessary.

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