Biostatistics PhD
Major: Biostatistics
Degree Awarded: Doctor of Philosophy (PhD)
Calendar Type: Quarter
Minimum Required Credits: 90.0 (post-bachelor's) or 57.0 (post-master's)
Co-op Option: None
Classification of Instructional Programs (CIP) code: 26.1102
Standard Occupational Classification (SOC) code: 15-2041
About the Program
The Doctor of Philosophy in Biostatistics trains highly functional statistical researchers with the breadth of knowledge to contribute to many applied domains or to specialize in a single theoretical domain. Students will receive a strong, quantitative foundational core in statistical theory while simultaneously having opportunities to apply these concepts to a wide range of practical applications. An important feature of the program is deliberate exposure to more contemporary quantitative concepts in data science.
The program will offer interdisciplinary instruction and research opportunities that are designed to provide a solid training in both statistical theory and in applications of biostatistical methods to a variety of relevant contexts that are central to modern interdisciplinary research. The program will prepare students for successful careers in academia (both teaching and research), government agencies, private health-related organizations/industries, and many other data-driven industries.
Students will take a comprehensive exam that requires them to synthesize coursework and demonstrate mastery of public health competencies. Students will then develop and defend a dissertation proposal and complete a dissertation of publishable quality and final defense.
Post-Baccalaureate Requirements and Post-Master's Requirements
Both post-baccalaureate and post-master's students are admitted into the doctoral program in Biostatistics.
For post-master’s students in a related field, students must complete a minimum of 57.0 credits.
For post-baccalaureate students, students must complete a minimum of 90.0 credits.
Major Competencies
- Master fundamental concepts in probability and statistical theory
- Construct an analysis plan to evaluate a scientific question of interest
- Critically appraise statistical methods literature
- Communicate statistical findings effectively and succinctly using data visualization tools and appropriate summaries
- Direct quantitative methods of collaborative investigations with researchers in public health, medicine, and other health science disciplines
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 701 | Advanced Statistical Computing * | 3.0 |
BST 751 | Statistical Inference I * | 3.0 |
BST 804 | Applied Bayesian Analysis | 3.0 |
BST 819 | Statistical Machine Learning for Biostatistics | 3.0 |
BST 823 | Theory of Generalized Linear and Mixed Models | 3.0 |
BST 825 | Probability Models and Stochastic Processes | 3.0 |
BST 826 | Research Skills in Biostatistics I | 1.0 |
BST 827 | Research Skills in Biostatistics II | 1.0 |
BST 828 | Research Skills in Biostatistics III | 1.0 |
BST 851 | Statistical Inference II * | 4.0 |
BST 867 | Statistical Consulting | 3.0 |
BST 869 | Linear Statistical Models * | 4.0 |
BST 870 | Generalized Linear Models * | 4.0 |
BST 875 | Statistical Consulting Lab (taken 3 times ) | 3.0 |
MATH 510 | Applied Probability and Statistics I * | 3.0 |
EPI 570 | Introduction to Epidemiology * | 3.0 |
RCRG 600 | An Introduction to the Responsible Conduct of Research | 0.0 |
PBHL 501 | Introduction to Public Health ** | 0.0 |
Dissertation | 33.0 | |
Biostatistics Thesis Research | ||
Electives (Choose Two) | 6.0 | |
Longitudinal Data Analysis | ||
Survival Data Analysis | ||
Design & Analysis of Clinical Trials | ||
Nonparametric and Semiparametric Models | ||
Advanced Clinical Trials | ||
Advanced Bayesian Analysis | ||
Causal Inference in Epidemiology: Theory | ||
Probability Theory I | ||
Probability Theory II | ||
Topics in Probability Theory | ||
Selectives (Choose two) | 6.0 | |
Applied Multivariate Analysis | ||
Making Sense of Data | ||
Data Science Using R | ||
or EPI 864 | Data Science Using R | |
Introduction to GIS for Public Health | ||
Topics in Computer Simulation | ||
Total Credits | 90.0 |
- *
Students entering the PhD program with a master's degree in a related field may be waived from these classes, as determined by the PhD Biostatistics Admissions Committee.
- **
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
First Year | |||||||
---|---|---|---|---|---|---|---|
Fall | Credits | Winter | Credits | Spring | Credits | Summer | Credits |
BST 869 | 4.0 | BST 751 | 3.0 | BST 804 | 3.0 | Written Qualifying Exam | |
EPI 570 | 3.0 | BST 825 | 3.0 | BST 823 | 3.0 | ||
MATH 510 | 3.0 | BST 870 | 4.0 | BST 851 | 4.0 | ||
PBHL 501* | 0.0 | ||||||
10 | 10 | 10 | 0 | ||||
Second Year | |||||||
Fall | Credits | Winter | Credits | Spring | Credits | Summer | Credits |
BST 826 | 1.0 | BST 819 | 3.0 | BST 701 | 3.0 | Oral Candidacy Exam | |
BST 867 | 3.0 | BST 827 | 1.0 | BST 828 | 1.0 | ||
BST 875 | 1.0 | BST 875 | 1.0 | BST 875 | 1.0 | ||
BST 999 | 3.0 | RCRG 600 | 0.0 | BST 999 | 3.0 | ||
PBHL 501 | 0.0 | Elective or Selective | 3.0 | Elective or Selective | 3.0 | ||
Elective or Selective | 3.0 | Elective or Selective | 3.0 | ||||
11 | 11 | 11 | 0 | ||||
Third Year | |||||||
Fall | Credits | Winter | Credits | Spring | Credits | ||
BST 999 | 9.0 | BST 999 | 9.0 | BST 999 | 9.0 | ||
9 | 9 | 9 | |||||
Total Credits 90 |
- *
PBHL 501 is only required for students who do not have a degree from a CEPH accredited school.
Alternative Plan of Study
(Students entering the PhD program with a master's degree in a related field, as determined by the PhD Biostatistics Admissions Committee)
First Year | |||||||
---|---|---|---|---|---|---|---|
Fall | Credits | Winter | Credits | Spring | Credits | Summer | Credits |
BST 826 | 1.0 | BST 819 | 3.0 | BST 804 | 3.0 | Written Qualifying Exam and Oral Candidacy Exam | |
BST 867 | 3.0 | BST 825 | 3.0 | BST 823 | 3.0 | ||
PBHL 501* | 0.0 | BST 827 | 1.0 | BST 828 | 1.0 | ||
Elective or Selective | 3.0 | Elective or Selective | 3.0 | Elective/Selective | 3.0 | ||
Elective or Selective | 3.0 | ||||||
10 | 10 | 10 | 0 | ||||
Second Year | |||||||
Fall | Credits | Winter | Credits | Spring | Credits | ||
BST 875 | 1.0 | BST 875 | 1.0 | BST 875 | 1.0 | ||
BST 999 | 8.0 | BST 999 | 8.0 | BST 999 | 8.0 | ||
RCRG 600 | 0.0 | ||||||
9 | 9 | 9 | |||||
Total Credits 57 |
- *
PBHL 501 is only required for students who do not have a degree from a CEPH accredited school.