Academic Programs

The doctoral degree (PhD) in Biostatistics prepares individuals to understand the mathematical and theoretical basis of statistical methodology; collaborate on the design of research studies in the health sciences; provide advice on the proper collection, entry, storage, retrieval, and manipulation of data; and take primary responsibility for the analysis, interpretation and dissemination of data in a research study using state-of-the-art statistical methods and software. PhD students are also prepared to carry out original methodological research in statistics and apply the resulting methodology to health-related research problems. 

General Information
The PhD program curriculum includes

• Didactic coursework
• 40 hours of core coursework
• 21 hours of elective coursework with at least 9 credit hours at the 9000-level
• Preliminary and Comprehensive Exams, and
• Dissertation of original methodological statistical research applicable to the health sciences

Funding for PhD Students
We offer a Graduate Research Assistantship to competitive PhD students that consists:

• A $20,000 stipend for 9-month at the beginning years and a $25,000 yearly stipend for later years in the program
• Student health insurance for a single adult, and
• Tuition reduction to $25 per semester. 

Graduate Research Assistants provide statistical consulting support as well as methodological statistical work with their mentor in order to gain practical application and methodological development skills on real world applications of biostatistics in the health sciences.

Year	Fall	Spring	Summer
1	STAT 7110 – Statistical Models and Methods (3) STAT 7520 – Stat Theory I (3) DATS 7510 –Programming for Data Analysis (3) BIOM 8011 – RCR (1)	STAT 7630 – Applied Linear Models (3) STAT 7620 – Stat Theory II (3) Elective (3) Elective (3)	No summer courses are required. Enrolling in Stat 8890 RR Is optional (without summer funding). Year 1: 16 hrs core, 6 hrs elect
2	STAT 9220 Advanced Stat Inference (3) or STAT 9120 – Theory of Linear Models (3) STAT 7640 – Gen Linear Models I (3) STAT 7720 Survival Analysis (3) STAT 7870 – Biostat Consulting Research (3)	STAT 9140 -Gen Linear Models II (3) or STAT 9240 – Bayesian Inference (3) DATS 8170 – Advanced Comp Methods (3) Elective (3) Elective (3)	No summer courses are required. Enrolling in Stat 8890 RR Is optional (without summer funding). Year 2: 18 hrs core, 6 hrs elect
3	STAT 9220 Advanced Stat Inference (3) or STAT 9120 – Theory of Linear Models (3) Elective (3) Electives (3) STAT 8890 – RR (3) 1st attempt Comp Exam: 1st and 2nd wks in fall. 2nd attempt: 2 wks before end of the fall semester.	STAT 9140 – Gen Linear Models II (3) or STAT 9240 – Bayesian Inference (3) Elective (3) STAT 8890 – RR (6)	No summer courses are required. Enrolling in Stat 8890 RR is optional (without summer funding). Year 3: 6 hrs core, 9 hrs. elect, 9 RR
4	STAT 8890 – RR (9-12) Proposal due (1st attempt)	STAT 9300 –Dissertation Res (DS) [Enrollment in 9300 requires pass of the Proposal] (9) or STAT 8890 RR (9) Proposal due (2nd attmpt)	STAT 9300 – DS (12) Year 4: 9 - 21 hrs RR, 12-21 hrs DS
5	STAT 9300 – DS (12)	STAT 9300 – DS (12)	STAT 9300 – DS (12) Year 5: 24 - 36 hrs DS

Notes: 

• The Doctor of Philosophy curriculum is not lock-step; students do not graduate as a class at the end of the specific semester.
• The maximum duration of the program is 7 years.
• STAT 9300 – Dissertation Research must be taken every semester after admission to the candidacy until dissertation requirements are met.
• Funding (GRA) for Biostatistics PhD students is only available for up to 5 years contingent upon students’ performance and availability of funds.

Suggested Elective Courses (21 credit hours with at least 6 credit hours at the 8000-level or above with prefix STAT or DAT)

• STAT 7130 Introduction to Epidemiology 3 CR
• STAT 7240 Introduction to Clinical Trials 3 CR
• STAT 7260 Design and Analysis of Observational Studies 3 CR
• STAT 7350 Epidemic Modeling 3 CR
• STAT 7360 Systematic Reviews 3 CR
• STAT 7370 Intermediate Epidemiology 3 CR
• DATS 7530 Computing for Data Science 3 CR
• STAT 7650 Introduction to Stochastic Processes 3 CR
• STAT 7670 Modern Methods of Multivariate Analysis 3 CR
• STAT 7740 Design & Analysis of Clinical Trials 3 CR
• STAT 7750 Introduction to Genetic Analysis 3 CR
• DATS 7760 Data & Visual Analytics 3 CR
• STAT 7850 Omics Data Analysis 3 CR
• DATS 7860 Statistical and Machine Learning for Big Data 3 CR
• STAT 7880 Special Topics 1-3 CR
• STAT 8150 Advanced Genomic Data Analysis 3 CR
• STAT 8160 Analysis of Clustered and Correlated Data 3 CR
• STAT 8231 Nonparametric & Robust Statistical Methods 3 CR
• STAT 8270 Computational Genomics & Proteomics 3 CR
• STAT 9280 Advanced Special Topics 1-3 CR