Courses
The listing of a course description here does not guarantee a course’s being offered in a particular semester. Please refer to the published schedule of classes on the MyBU Student Portal for confirmation a class is actually being taught and for specific course meeting dates and times.
View courses in
- SPH BS 401: Survey in Biostatistical Methods
Course This course is offered through the Summer Institute in Biostatistics (SIBS) Program and is not for graduate credit. The objectives of this course are to introduce undergraduate students accepted to the program to biostatistics as a vibrant, vitally important discipline that provides essential tools for biomedical research and offers many exciting possibilities as a career. Students will learn the basic principles of biostatistical analysis, epidemiological analysis, design and analysis of clinical trials and statistical genetics. The course also includes an introduction to the SAS computing package and exposure to NHLBI studies of heart, lung, blood, and sleep disorders to illustrate the management, analysis and reporting of data. The class is offered in June and July. - SPH BS 700: Essentials of Biostatistics
This intensive one-week course provides a comprehensive introduction to the use of biostatistics in the field of public health. Students learn to compute and interpret descriptive and inferential statistics. Topics include descriptive statistics and graphical displays of data, probability, confidence intervals, hypothesis testing for means and proportions, linear and logistic regression and survival analysis. - SPH BS 704: Introduction to Biostatistics
This course provides an overview of biostatistical methods, and gives students the skills to perform, present, and interpret basic statistical analyses. Topics include the collection, classification, and presentation of descriptive data; the rationale of estimation and hypothesis testing; analysis of variance; analysis of contingency tables; correlation and regression analysis; multiple regression, logistic regression, and the statistical control of confounding; sample size and power considerations; survival analysis. Special attention is directed to the ability to recognize and interpret statistical procedures in articles from the current literature. Students will use the R statistical package to analyze public health related data. * Can't be taken together for credit with SPH PH 717 - SPH BS 715: Practical Skills for Biostatistics Collaboration
- SP
- SPH BS 722: Design and Conduct of Clinical Trials
This course covers the development, conduct, and interpretation of clinical trials. It is suitable for concentrators in any department. Topics include principles and practical features such as choice of experimental design, choice of controls, sample size determination, methods of randomization, adverse event monitoring, research ethics, informed consent, data management, and statistical analysis issues. Students write a clinical trial protocol during the semester. - SP
- SPH BS 728: Public Health Surveillance,a Methods Based Approach
Thacker wrote, "Surveillance is the cornerstone of public health practice." This course will provide an introduction to surveillance and explore its connections to biostatistics and public health practice. Topics will include complex survey design, weighted sampling, capture-recapture methods, time series analyses and basic spatial analyses. Students will learn about available surveillance data, how to analyze these data, and how to write about their findings. This class carries Epidemiology concentration credit. - SP
- SPH BS 740: Design and Conduct of Public Health Research
This course provides practical experience with the theory and process of public health research. Topics include an overview of study design, principles of sampling and randomization, human subject issues and informed consent, the role of the IRB, qualitative research design and practice, and data management. This is a required course for the Design and Conduct of Public Health Research Certificate. - SPH BS 750: Essentials of Quantitative Data Management
Any data analysis is only as good as the data on which it is based. This course will focus on the importance of high quality data and the skills required for effective data management, including collection, cleaning, auditing, and merging. Students will have hands-on experience with data sets. Examples of what can go wrong and how research can be complicated by or produce erroneous results due to poor quality data will be provided. - SPH BS 755: Linear Models
Post-introductory course on linear models. Topics to be covered include simple and multiple linear regression, regression with polynomials or factors, analysis of variance, weighted and generalized least squares, transformations, regression diagnostics, variable selection, and extensions of linear models. Effective Fall 2023, this course fulfills a single unit in the following BU Hub area: Quantitative Reasoning II, Teamwork/Collaboration. - SPH BS 771: Topics in Biostatistics
Two and four credit topics courses may be offered throughout the academic year as a means of exploring new areas of study in the discipline. Topics vary by semester. Please refer to the print schedule for the specific course in any given semester. Not taught every year or semester. - SP
- SPH BS 795: Seminar in Ci
- SP
- SPH BS 803: Statistical Programming for Biostatisticians
This course will focus on skills required for advanced computing applications in biostatistics. Students will learn statistical programming and methods such as loops, functions, macros as well as data visualization techniques in SAS and R. Furthermore, the course will provide and introduction to Linux and basic statistical programming in Python. Lab sessions S will also provide students with basic computing skills to enroll to more advanced statistical classes such as BS830 and BS857. - SPH BS 805: Intermediate Statistical Computing and Applied Regression Analysis
This course is a sequel to BS723. Emphasis is placed on the use of intermediate-level programming with the SAS statistical computer package to perform analyses using statistical models with emphasis on linear models. Computing topics include advanced data file manipulation, concatenating and merging data sets, working with date variables, array and do-loop programming, and macro construction. Statistical topics include analysis of variance and covariance, multiple linear regression, principal component and factor analysis, linear models for correlated data, and statistical power. Includes a required lab section. - SPH BS 806: Multivariable Analysis for Biostatisticians
This course will focus on skills required for effective conduct of data analysis with statistical packages, primary with R. This course will focus on the multiple regression modeling and multivariate analysis to cover multi-way ANOVA, multiple linear regression, classification and regression trees, automated model search, model fit and diagnostic, and multivariate analysis (PCA and cluster analysis) with particular emphasis on applications in medicine and public health. - SPH BS 807: Applied Causial Inference in Health Research
This is an advanced statistics course, focused on application of causal inference methods in medical research. Topics covered include counterfactual outcomes, causal diagrams, mediation analysis, instrumental variable, and g- methods to deal with time-varying confounding. This course includes lectures, computer instructions, and discussion of reading material.
