Course Information for the Biostatistics M.S.
At Grand Valley professional biostatisticians are prepared for leadership in the biological and health sciences industries and benefit from valuable internship experiences and placement of graduates. Suggested Course sequences and course descriptions are listed below.
Click for a list of suggested prerequisite courses
Suggested Course Sequence
Year One, Fall Semester
STA 610, CIS 661, Elective* or PSM Core Course
Year One, Winter Semester
STA 616, STA 623, Elective* or PSM Core Course
Year Two, Fall Semester
PSM 662, STA 621, Elective* or PSM Core Course or PSM 691**
Year Two, Winter Semester
STA 625, STA 630, Elective, PSM 691**
*Common fall electives are STA 518 (R Programming), BMS 523 (Epidemiology)
*Common winter electives are STA 628 (survival analysis), STA 526 (multivariate analysis)
**Internships can be completed during the spring/summer semester or during either semester of the second year
-- Note: PSM 650 or PSM 691 can be taken in the spring/summer term
The Professional M.S in Biostatistics consists of 37 credits with a minimum cumulative GPA of 3.0.
Common Courses in Professional Science Masters
- STA 610 Applied Statistics for Health Professions (3 cr)
Project-oriented overview of major statistical techniques commonly used in problems encountered in health professions. Students will learn to use a major statistical computing package. Hypothesis testing, t-tests, regression, analysis of variance, analysis of covariance, categorical data analysis, nonparametric statistics.
- CMB 610 Foundations of Biotechnology (3 cr)
Introduction to the methods and strategies used for the manipulation of biological systems to produce food, drugs, and other products. Topics include experimental systems, gene and protein analysis, genetic engineering, recombinant DNA technology, transgenic organisms, gene therapy, and plant biotechnology.
- CIS 661 Introduction to Medical and Bioinformatics (3 cr)
A survey of fundamental concepts of medical and bioinformatics methods and techniques involved in the integration of computer systems in medical centers and life science industries. Introduction to biomedical information systems; data representation, modeling, management and mining; systems evaluation; project management practices for biomedical decision making. Legal and ethical considerations.
- PSM 650 Ethics and Professionalism in Applied Science (3 cr)
Ethical and professional issues and problems facing practicing scientists. Emphasizes and role of scientists in public and private sectors, their responsibilities, and emerging ethical and professional issues.
(The seminar course is an important inter-disciplinary opportunity for the PSM programs)
- PSM 662 (2 cr)
A seminar course designed to broaden the student's professional foundation in the practice of applied sciences following industry "best practices". Project management practice; intellectual property and proprietary issues; industrial policies and procedures; and governmental regulatory issues are examined. Focus on team building, networking, and communication and presentation skills.
- STA 616 Statistical Programming (3 cr)
Provides intensive instruction in the use of SAS to prepare data for statistical analysis. Topics include: importing/exporting data in various formats; character and numeric manipulation; merging, setting and combining datasets; effective programming skills using arrays, loops and macros; creating graphs; producing reports.
- STA 621 Design of Experiments and Regression (4 cr)
Design and analysis of single- and multiple factor experiments. Includes block designs, repeated measures, factorial and fractional factorial experiments, response surface experimentation. Techniques include simple and multiple linear regression, repeated measures, generalized linear models, correlation, model building diagnosis. Applications in biological and biomedical problems. A computer package will be used.
- STA 623 Categorical Data Analysis (3 cr)
A study of regression models for the analysis of categorical data: logistic, probit and complementary log-log models for binomial random variables; log-linear models for cross-classification of counts; regression models for Poisson rates; and multinomial responses models for both nominal and ordinal responses. Model specification and interpretation are emphasized.
- STA 625 Clinical Trials (2 cr)
This course is designed for individuals with a quantitative background who are interested in the scientific, policy, design and management aspects of clinical trials. Topics include types of treatment allocation and randomization, patient recruitment and adherence, power and sample size, interacting with monitoring committees, administering multicenter trials, and study closeout.
- STA 630 Perspectives in Advanced Biostatistics (3 cr)
Reflecting on the knowledge and skills acquired throughout the biostatistics program and internship, this course examines the responsibilities of a professional biostatistician. This course will also examine current topics in biostatistics including survival analysis (including Kaplan-Meier estimation), sequential analysis of emerging data, bioequivalence, analysis of health surveys, and Bayesian methods.
- PSM 691 (minimum of 4 credits, taking place in a partnering workplace organization, supervised by GV faculty to meet properly outlined criteria and objectives)