Each track in the MS in Biostatistics Program curriculum consists of at least 34 credits which must be completed in one full-time academic year. In addition to coursework, students will complete a capstone project in each term. This section covers the following:

Theory and Methods Track

Students are expected to take a total of five required courses (12 credits) in the Fall Term, five required courses (13 credits) in the Spring I Term, and three required courses (7 credits) in the Spring II Term. In addition to the 32 credits of required coursework, students must take at least two clinical research-related elective credits, yielding the 3-credit minimum to successfully complete the MS in Biostatistics Program in one year. Required coursework is indicated in bold below.

Fall

• BIO6000 Capstone 1 MS Biostatistics - 1 credit

• BIO6100 Fundamentals of Epidemiology - 3 credits

• BIO6300 Introduction to R Programming - 2 credits

Spring I

• BIO8000 Capstone 2 MS Biostatistics - 1 credit

• BIO8200 Analysis of Categorical Data - 3 credits

• BIO8400 Advanced Statistical Methods in Clinical Research - 3 credits

Spring II

• BIO9000 Capstone 3 MS Biostatistics - 1 credit

• BIO9100 Survival Analysis - 3 credits

• BIO9200 Analysis of Longitudinal Data - 3 credits

Required credits 32 Minimum elective credits 2 Total credits 34

Students are expected to take a total of five required courses (11 credits) in the Fall Term, five required courses (12 credits) in the Spring I Term, and four required courses (7 credits) in the Spring II Term. In addition to the 30 credits of required coursework, students must take at least three clinical research-related elective credits, yielding the 34-credit minimum to successfully complete the MS in Biostatistics Program in one year. Required coursework is indicated in bold below.

Fall

• BIO6000 Capstone 1 MS Biostatistics - 1 credit

• BIO6100 Fundamentals of Epidemiology - 3 credits

• BIO6400 Biostatistics for Biomedical Research - 3 credits

• BIO6500 Probability and Inference 1 - 3 credits

• CLR6100 Clinical Trial Management - 1 credit

• BIO6300 Introduction to R Programming - 2 credits

• BDS1005 Computer Systems: UNIX/LINUX Fundamentals - 1 credit*

• BDS1006 Computer Systems: Architecture & Applications - 1 credit*

• BDS1007 Computer Systems: Intro to Scientific Programming Python - 1 credit* *Must seek course director's approval prior to registering

Spring I

• BIO8000 Capstone 2 MS Biostatistics - 1 credit

• BIO8200 Analysis of Categorical Data - 3 credits

• BIO8700 Theory of Linear & Generalized Linear Models - 3 credits

Spring II

• BIO9000 Capstone 3 MS Biostatistics - 1 credit

• BIO9001 Applied Analysis of Healthcare Databases - 3 credits

• MPH0822 Applied Linear Models 2 - 3 credits

Required credits 30 Minimum elective credits 4 Total credits 34

This chapter covers the MS in Biostatistics Program. Students can find the following information in this section.

• Program Information

• Program Requirements

  • Curricular Requirements

  • Requirements to Graduate

  • Standards for Maintaining Satisfactory Progress

  • Advising

• • Theory and Methods Track

  • Clinical Applications Track

Program Website

http://icahn.mssm.edu/education/masters/biostatistics

Co-Directors

Emilia Bagiella

Alan Weinberg

Program Description

Presented in a one-year, full-time format, the MS in Biostatistics program offers students rigorous, comprehensive didactic training in high-quality clinical and translational research. Our curriculum provides students with strong quantitative training as well as practical strategies for addressing complex challenges of novel, clinical research. The program also helps students hone their critical thinking skills. The program’s structure provides students with the opportunity to gain excellent mentorship and individualized attention from faculty in biostatistics and a variety of other disciplines.

The Master of Science in Biostatistics program provides students with the fundamental skills required for conducting high-quality clinical and translational research. The curriculum emphasizes strong quantitative training, critical thinking skills, and practical strategies for addressing complex challenges in clinical research.

The Theory and Methods Track is aimed at students whose goal is to work as biostatisticians or data analysts in a clinical, research, or industry setting. It can also be used as a stepping stone to pursuing a PhD in Biostatistics or Epidemiology. Applicants do not need to have a background related to a health or clinical field, but a strong quantitative background is required.

The Clinical Applications Track is designed for clinical and translational investigators who want to acquire knowledge of quantitative methods in clinical research. A strong quantitative background and a degree in Medical Sciences (MD, DDS, DMD, ND, or DO) are required to apply to this track. Each track in the program consists of at least 34 credits and must be completed in one full-time year. There are two parts: a course requirement and a capstone requirement.

Program Learning Objectives Upon successful completion of the MS in Biostatistics program, graduates will be able to:

1. Apply advanced statistical methods to the design, analysis, and interpretation of clinical and translational research studies, using rigorous and practical approaches grounded in biostatistical theory.

2. Operationalize conceptual research questions into testable hypotheses and determine the most appropriate analytical methods to evaluate those hypotheses in real-world research settings.

3. Conduct advanced statistical analyses using modern computational tools and techniques, while demonstrating proficiency in statistical programming and data management.

Capstone-related lectures and projects will:

• Engage students in important discourse surrounding data management and research ethics

• Challenge students to turn conceptual research questions into testable hypotheses and to determine the appropriate analytic testing methods

• Provide students with the opportunity to shadow Biostatistics faculty mentors in the Center for Biostatistics consultation service

Additionally, students will learn how to create appropriate study design-related and methodological solutions to cutting edge, real-world research questions. Students will conduct advanced preliminary analyses under the guidance and supervision of their mentors. At the end of the Spring II term students will communicate their findings to an institution-wide audience at an MS in Biostatistics Capstone Symposium.

Program Requirements

Each track in the MS in Biostatistics Program curriculum consists of at least 34 credits which must be completed in one full-time academic year. In addition to coursework, students will complete a capstone project in each term.

For the Theory and Methods Track, students will earn a grade of B or higher in two semesters of college-level calculus and at least one college-level linear algebra course.

For the Clinical Applications Track, students will earn a grade of B or higher in at least one semester of college-level calculus and one college-level linear algebra course, and applicants must be clinical professionals. If an applicant hasn’t yet taken a college-level linear algebra course as an undergraduate, upon acceptance to the program, they will have to successfully complete this course prior to enrollment.

Milestones

• Students will be asked to declare a Capstone mentor and a project by February 15.

• Capstone Declaration Form should be completed by each student and signed by their Capstone Mentor.

Graduation Requirements

• Students need to complete the entire sequence of courses to graduate.

• Students need to successfully complete a Capstone before the year ends by graduation.

Standards for Maintaining Satisfactory Progress

MS in Biostatistics students maintain satisfactory progress by:

• Matriculating on a full-time basis

• Maintaining a minimum cumulative GPA of 3.0.

• Meeting with faculty advisors at least twice in the fall term, and at least once per term thereafter

Advising

Each student will be assigned to a full-time faculty member for the year based upon their research goals.