PhD in Biostatistics Requirements & Courses

The objective of the PhD degree program is to provide students with the quantitative skills needed for the development, evaluation and application of novel methods for the analysis of modern biomedical data. 51 credits beyond the Master’s degree are required

  • 22 credits core courses required
  • 5 credits electives
  • 24 dissertation credits

 Additional Requirements

Non-credit Requirements

  • Doctoral students are required to participate in a monthly Ph.D. Journal Club over the course of four (4) semesters.
  • Students are also expected to attend the department’s Epidemiology and Biostatistics Seminar Series each semester.
  • After earning an MS or MPH in Epi, students have up to 8 years to complete all requirements and successfully defend their doctoral dissertation.

Course Options 

The PhD program will offer an emphasis in three broad (Concentration) areas:

  • Concentration/Emphasis 1: Design and Analysis of Medical Studies
  • Concentration/Emphasis 2: Big Data and Statistical Genetics
  • Concentration/Emphasis 3: Biometry
1. Complete all of the required 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 required 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 821B Cross Section and Panel Data Econometrics I 3
EC 821 Cross Section and Panel Data Econometrics II 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 821B Cross Section and Panel Data Econometrics I 3
EC 821 Cross Section and Panel Data Econometrics II 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 821B Cross Section and Panel Data Econometrics I 3
EC 821 Cross Section and Panel Data Econometrics II 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.

 

PhD Schedule

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Biostatistics