Biostatistics MS

Major: Biostatistics
Degree Awarded: Master of Science (MS)
Calendar Type: Quarter
Minimum Required Credits: 47.0
Co-op Option: None
Classification of Instructional Programs (CIP) code: 26.1102
Standard Occupational Classification (SOC) code: 15-2041

About the Program

Students in the Master of Science in Biostatistics program gain the skills necessary to apply statistical, mathematical, and computational techniques to scientific research in health-related fields, including medicine, epidemiology, and public health. Biostatistics is an integral and indispensable tool in improving health and reducing illness through efficient and appropriate analysis of data collected to answer health-related research questions. Biostatisticians play essential roles in designing studies and analyzing research data. MS graduates are often employed in public health research and service organizations, university research groups, hospitals, pharmaceutical companies, health-related industries, contract research organizations, policy think tanks, foundations, and government. The demand for biostatisticians in the job market has been consistently strong and growing for the past decade. New technologies are generating an unprecedented amount of data which present exciting opportunities for biostatisticians with strong computational skills.

The program provides students with a thorough understanding of biostatistical methods, strong computational and communication skills, and the ability to apply this knowledge to research focusing on health-related problems. The program equips students with the relevant skills to handle the quantitative and computational aspects of a research project including study design, data collection and management, developing analysis plans, conducting analyses, and reporting findings both orally and in writing. Coursework includes statistical theory and methods, computing and data management, epidemiology, and general public health topics. A highlight of the program is the incorporation of a faculty-guided practicum experience working on a real academic, government, or industry project in a sponsoring organization setting. The practicum-based research project will involve the application of biostatistical analysis to a problem of significance to the sponsoring academic, government, or industry organization with joint oversight provided by a department faculty member and an on-site PhD-level biostatistician.

Additional Information

For more information about this program, please contact:

DSPH Academic Advising Team
Office of Education
dsphadvising@drexel.edu

Additional information can be found on the Dornsife School of Public Health website, including admissions criteria and how to apply.

Degree Requirements

Required Courses
BST 522Introduction to Probability for Biostatistics3.0
BST 551Statistical Inference I3.0
BST 553Longitudinal Data Analysis3.0
BST 555Introduction to Statistical Computing3.0
BST 557Survival Data Analysis3.0
BST 567Statistical Collaboration3.0
BST 569Linear Statistical Models4.0
BST 570Generalized Linear Models4.0
BST 675Statistical Collaboration Lab3.0
BST 701Advanced Statistical Computing3.0
EPI 570Introduction to Epidemiology3.0
PBHL 501Introduction to Public Health *0.0
Master's Project
Select one from the following:3.0
Statistical Collaboration in Practice
Data Analysis Project
Electives
Select from the list below:9.0
Any (BST) Biostatistics 500-999 level course
Any (EPI) Epidemiology 500-999 level course
Total Credits47.0
*

Foundational Public Health Learning Objectives: PBHL 501 is only required for students who do not have a degree from a CEPH accredited school.

Sample Plan of Study

Plan of Study Grid
First Year
FallCredits
BST 522 Introduction to Probability for Biostatistics 3.0
BST 569 Linear Statistical Models 4.0
EPI 570 Introduction to Epidemiology 3.0
 Credits10
Winter
BST 551 Statistical Inference I 3.0
BST 555 Introduction to Statistical Computing 3.0
BST 570 Generalized Linear Models 4.0
 Credits10
Spring
BST 701 Advanced Statistical Computing 3.0
Electives 6.0
 Credits9
Summer
VACATION  
 Credits0
Second Year
Fall
BST 557 Survival Data Analysis 3.0
BST 567 Statistical Collaboration 3.0
BST 675 Statistical Collaboration Lab 3.0
PBHL 501 Introduction to Public Health * 0.0
 Credits9
Winter
BST 553 Longitudinal Data Analysis 3.0
BST 698
Statistical Collaboration in Practice
or Data Analysis Project
3.0
Electives 3.0
 Credits9
 Total Credits47
*

PBHL 501 is only required for students who do not have a degree from a CEPH accredited school.

Program Level Outcomes

Major Competencies

Upon completion of the program, graduates will be prepared to:

  • Apply appropriate quantitative methods to evaluate the determinants and epidemiology of health and disease
  • Manage and maintain analytic datasets
  • Execute a data analysis plan
  • Communicate statistical findings effectively and succinctly using data visualization tools and appropriate summaries
  • Work collaboratively with researchers in public health, medicine, and other health science disciplines