# Biostatistics PhD

*Major: Public Health*

*Degree Awarded:* Doctor of Philosophy (PhD)

*Calendar Type: Quarter*

*Total Credit Hours:* 86.0

Co-op Option*: None*

*Classification of Instructional Programs (CIP) code:* 26.1102

*Standard Occupational Classification (SOC) code:* 15-2041

## About the Program

The PhD in biostatistics will train highly functional statistical researchers with the breadth of knowledge to contribute to many applied domains or to specialize in a single theoretical domain. Students should expect to 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 our new program is deliberate exposure to more contemporary quantitative concepts in data science.

The doctoral program in biostatistics 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. This program will prepare doctoral students for successful careers in academia (both teaching and research), government agencies, private health-related organizations/industries and many other data-driven industries.

### Additional Information

For additional information about the program, visit the Dornsife School of Public Health web site.

## Admission Requirements

Applicants must have a Bachelor’s or a Master’s degree from an accredited institution and must satisfy general Drexel University School of Public Health requirements for admission. Admission to the PhD program in biostatistics is based on:

1. A strong academic background in mathematics, statistics, and related sciences, and practical, professional, or research experience. Background in mathematics should include one year of calculus including multivariate calculus, linear algebra, and a calculus-based course in probability or statistics. Additional background in biological, social, or health sciences is desirable.

2. Three letters of recommendation.

3. GRE scores for the General Test.

4. TOEFL/IELTS scores are required for all applicants whose native language is not English. If an international applicant has attended a US institution of higher education for two or more years of consecutive enrollment, this TOEFL requirement will be waived.

5. Statement of purpose.

6. Official transcripts of all post-secondary school course work completed or attempted.

PhD applicants in biostatistics traditionally have an undergraduate degree in mathematics or statistics, but students with degrees in other fields, in particular data science, computer science or engineering, will be considered with the requirement that necessary mathematical course work must be completed. Applicants must have at least a B+ average in courses required as prerequisites for the program. We will require that PhD students should have strong mathematical background, which includes having completed courses such as multivariate calculus, real analysis, and linear algebra, familiarity with probability and statistics. Additionally, exposure to statistical programming is highly desirable.

## Degree Requirements

Required Courses | ||

BST 551 | Statistical Inference I | 3.0 |

BST 567 | Statistical Consulting | 3.0 |

BST 569 | Linear Statistical Models | 4.0 |

BST 570 | Generalized Linear Models | 3.0 |

BST 604 | Applied Bayesian Analysis | 3.0 |

BST 623 | Theory of Generalized Linear and Mixed Models | 3.0 |

BST 625 | Probability Models and Stochastic Processes | 3.0 |

BST 626 | Research Skills in Biostatistics I | 1.0 |

BST 627 | Research Skills in Biostatistics II | 1.0 |

BST 628 | Research Skills in Biostatistics III | 1.0 |

BST 651 | Statistical Inference II | 4.0 |

BST 701 | Advanced Statistical Computing | 3.0 |

Non-credit Consulting Lab | ||

BMES 547 | Machine Learning in Biomedical Applications | 3.0 |

BST 999 | Biostatistics Thesis Research | 30.0 |

EPI 570 | Introduction to Epidemiology | 3.0 |

MATH 510 | Applied Probability and Statistics I | 3.0 |

PBHL 501 | Introduction to Public Health | 0.0 |

Electives (Choose Three) | 9.0 | |

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 | ||

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 | ||

Introduction to GIS for Public Health | ||

Topics in Computer Simulation | ||

Total Credits | 86.0 |

## Sample Plan of Study

Term 1 | Credits | |
---|---|---|

PBHL 501 | Introduction to Public Health | 0.0 |

Term Credits | 0.0 | |

Term 2 | ||

BST 569 | Linear Statistical Models | 4.0 |

EPI 570 | Introduction to Epidemiology | 3.0 |

MATH 510 | Applied Probability and Statistics I | 3.0 |

Term Credits | 10.0 | |

Term 3 | ||

BST 551 | Statistical Inference I | 3.0 |

BST 570 | Generalized Linear Models | 4.0 |

Elective or Selective | 3.0 | |

Term Credits | 10.0 | |

Term 4 | ||

BST 604 | Applied Bayesian Analysis | 3.0 |

BST 651 | Statistical Inference II | 4.0 |

BST 701 | Advanced Statistical Computing | 3.0 |

Term Credits | 10.0 | |

Term 5 | ||

BST 567 | Statistical Consulting | 3.0 |

BST 625 | Probability Models and Stochastic Processes | 3.0 |

BST 626 | Research Skills in Biostatistics I | 1.0 |

Elective or Selective | 3.0 | |

Term Credits | 10.0 | |

Term 6 | ||

BMES 547 | Machine Learning in Biomedical Applications | 3.0 |

BST 627 | Research Skills in Biostatistics II | 1.0 |

Electives or Selectives | 6.0 | |

Term Credits | 10.0 | |

Term 7 | ||

BST 623 | Theory of Generalized Linear and Mixed Models | 3.0 |

BST 628 | Research Skills in Biostatistics III | 1.0 |

BST 999 | Biostatistics Thesis Research | 3.0 |

Elective or Selective | 3.0 | |

Term Credits | 10.0 | |

Term 8 | ||

BST 999 | Biostatistics Thesis Research | 9.0 |

Term Credits | 9.0 | |

Term 9 | ||

BST 999 | Biostatistics Thesis Research | 9.0 |

Term Credits | 9.0 | |

Term 10 | ||

BST 999 | Biostatistics Thesis Research | 9.0 |

Term Credits | 9.0 | |

Total Credit: 87.0 |

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