Graduate Degree - Biostatistics - Doctor of Philosophy

Program:
Biostatistics - Doctor of Philosophy
Program Code:
2860 Biostatistics
Program Level:
Graduate
Award Type:
Doctor of Philosophy
Start Term:
FS17
College:
College of Human Medicine
Relevant Excerpt(s) from Academic Programs:
Department:
Department of Epidemiology and Biostatistics
Relevant Excerpt(s) from Academic Programs:


Excerpt from the official Academic Programs Catalog:

Listed below are the approved requirements for the program from the official Academic Programs Catalog.
Students must consult their advisors to learn which specific requirements apply to their degree programs.
Requirements as represented in Degree Navigator are not available for this program.

College of Human Medicine

Department of Epidemiology and Biostatistics

Graduate Study
Biostatistics - Doctor of Philosophy

The Doctor of Philosophy degree in Biostatistics provides students with the quantitative skills needed for the development, evaluation and application of novel methods for the analysis of modern biomedical data.

In addition to meeting the requirements of the university, and of the College of Human Medicine, students must meet the requirements specified below.

Admission

For admission to the doctoral degree in biostatistics on regular status, the student must:
  1. have a master’s degree in biostatistics, statistics, or related field;
  2. submit Graduate Record Examination (GRE)scores, or MCAT scores;
  3. provide TOEFL scores if their native language is other than English;
  4. provide three letters of recommendation;
  5. provide a statement of purpose;
  6. provide official transcripts.
Applicants with strong academic records who are in the process of completing a master of science may be admitted on a provisional basis. The first 33 credits applied towards the completion of a master of science may not be counted toward the Ph.D. in Biostatistics.

Applicants who are admitted without a master’s degree will be required to complete collateral course work to make up deficiencies. Collateral course work will not count towards the fulfillment of degree requirements. It is strongly recommended that applicants have taken course work in multivariate calculus, advanced undergraduate linear algebra and probability, and numerical computing.

Requirements for the Doctor of Philosophy Degree in Biostatistics

The doctoral degree program offers three concentration areas: design and analysis of medical studies; big data and statistical genetics; and ad biometry, a flexible option for students with diverse interests. The concentration is selected in consultation with a faculty advisor and guidance committee.

Students must:
1. Complete all of the following courses (13 credits):
EPI 810 Introductory Epidemiology 3
EPI 828 Seminar in Responsible Conduct of Research 1
EPI 860 Advanced Inference for Biostatistics 3
STT 867 Linear Model Methodology 3
STT 868 Mixed Models: Theory, Methods and Applications 3
2. Complete one of the following concentrations:
Design and Analysis of Medical Studies
1. One of the following courses (3 credits):
EPI 858 Clinical Trial I 3
EPI 952 Duration and Severity Analysis 3
Or
STT 847 Analysis of Survival Data 3
2. Complete 11 credits of elective course work:
ANS 814 Advanced Statistics for Biologists 4
CSE 331 Algorithms and Data Structures 3
CSE 480 Database Systems 3
CSE 482 Big Data Analysis 3
CSE 847 Machine Learning 3
CSE 881 Data Mining 3
EC 821A Cross Section and Panel Data Econometrics I 3
EC 821 Cross Section and Panel Data Econometrics II 3
EPI 812 Causal Inference in Epidemiology 3
EPI 855 Biostatistical Modeling in Genomic Data Analysis 3
EPI 880 Selected Topics in Biostatistics 3
EPI 920 Advanced Methods in Epidemiology and Applied Statistics 3
EPI 950 Advanced Biostatistical Methods in Epidemiology 3
EPI 952 Duration and Severity Analysis 3
EPI 953 Analytical Strategies for Observational Studies 3
EPI 990 Independent Study 3
STT 801 Design of Experiments 3
STT 825 Sample Surveys 3
STT 855 Statistical Genetics 3
STT 861 Theory of Probability and Statistics I 3
STT 862 Theory of Probability and Statistics II 3
STT 873 Statistical Learning and Data Mining 3
STT 874 Introduction to Bayesian Analysis 3
Additional courses may be chosen with advisor approval.
Big Data and Statistical Genetics
1. One of the following courses:
EPI 855 Biostatistical Modeling in Genomic Data Analysis 3
Or
STT 855 Statistical Genetics 3
CSE 231 Introduction to Programming I 3
Or
CSE 232 Introduction to Programming II 4
STT 456 Actuarial Models II 3
2. Complete 11 credits of elective course work:
ANS 814 Advanced Statistics for Biologists 4
CSE 331 Algorithms and Data Structures 3
CSE 480 Database Systems 3
CSE 482 Big Data Analysis 3
CSE 847 Machine Learning 3
CSE 881 Data Mining 3
EC 821A Cross Section and Panel Data Econometrics I 3
EC 821 Cross Section and Panel Data Econometrics II 3
EPI 812 Causal Inference in Epidemiology 3
EPI 858 Clinical Trials 3
EPI 880 Selected Topics in Biostatistics 3
EPI 920 Advanced Methods in Epidemiology and Applied Statistics 3
EPI 950 Advanced Biostatistical Methods in Epidemiology 3
EPI 952 Duration and Severity Analysis 3
EPI 953 Analytical Strategies for Observational Studies 3
EPI 990 Independent Study 3
STT 801 Design of Experiments 3
STT 825 Sample Surveys 3
STT 861 Theory of Probability and Statistics I 3
STT 862 Theory of Probability and Statistics II 3
STT 873 Statistical Learning and Data Mining 3
STT 874 Introduction to Bayesian Analysis 3
Additional courses may be chosen with advisor approval.
Biometry
1. Complete 14 credits of elective course work:
ANS 814 Advanced Statistics for Biologists 4
CSE 331 Algorithms and Data Structures 3
CSE 480 Database Systems 3
CSE 482 Big Data Analysis 3
CSE 847 Machine Learning 3
CSE 881 Data Mining 3
EC 821A Cross Section and Panel Data Econometrics I 3
EC 821 Cross Section and Panel Data Econometrics II 3
EPI 812 Causal Inference in Epidemiology 3
EPI 855 Biostatistical Modeling in Genomic Data Analysis 3
EPI 858 Clinical Trials 3
EPI 880 Selected Topics in Biostatistics 3
EPI 920 Advanced Methods in Epidemiology and Applied Statistics 3
EPI 950 Advanced Biostatistical Methods in Epidemiology 3
EPI 952 Duration and Severity Analysis 3
EPI 953 Analytical Strategies for Observational Studies 3
EPI 990 Independent Study 3
STT 801 Design of Experiments 3
STT 825 Sample Surveys 3
STT 847 Survival Analysis 3
STT 855 Statistical Genetics 3
STT 861 Theory of Probability and Statistics I 3
STT 862 Theory of Probability and Statistics II 3
STT 873 Statistical Learning and Data Mining 3
STT 874 Introduction to Bayesian Analysis 3
Additional courses may be chosen with advisor approval.
2. Attend all MSU Graduate School Responsible Conduct of Research (RCR) Workshops (human).
3. Attend 80% of department-sponsored Seminars.
4. Attend 80% of department Ph.D. Journal Club meetings.
5. Present at one Ph.D. Journal Club meeting.
6. Pass a comprehensive examination.
7. Complete 24 credits of EPI 999 Doctoral Dissertation Research.
8. Pass an oral defense of the doctoral dissertation.

Academic Standards

Students will sit for a comprehensive examination after the necessary course work is completed, typically at the end of the first year of study. A student who fails the comprehensive examination may repeat it only once. A retake examination will generally be given in January.