The program will prepare graduates needed in private and public sector research and health care settings who can apply statistical principles, processes, applications, and analytic methods to design, implement, and analyze health related studies including both experimental (clinical trials) and observational (epidemiological) studies.

Students must have taken a three- or four-semester calculus sequence and preferably a semester of linear algebra, or be willing to take them during matriculation.  Prior course work in statistics and probability is helpful, but not required.

The degree requirements of 38 semester credit hours include coursework in biostatistics and statistical theory and methods. Additionally, all biostatistics students are required to take a pass-fail seminar series in the college of medicine to become acquainted with the language and problems of medicine; and may take courses in other departments to meet the required credit hour requirements.  The course of study builds on a required set of courses that include a core set of biostatistics and statistical theory. The total academic credits required for graduation are 38 credit hours earned at a minimum of a 3.0 GPA with a maximum of 6 credit hours taken S/U. The curricular requirements are summarized:

 Biostatistical Core (3 3-credit courses)  9 credits
 Statistical Core (4 3-credit courses)  12 credits
 Elected requirements Biostatistics/Statistics 12 credits
 Required medical seminar   2 credits
 Electives     3 credits

Biostatistical Core Courses.  This requirement may be met by taking the three required core courses:

 STA 5172 Statistics for Epidemiology
 STA 5244 Controlled Clinical Trials
 STA 5938 Topics in Medical Consulting

Statistical Core Courses.  This requirement may be met by taking the four required core courses:

 STA 5166-7 Statistics in Applications I - II
 STA 5325 Mathematical Statistics
 STA 5326 Distribution Theory and Inference

Biostatistical/Statistical Elective Requirements.  In addition to the core courses in biostatistics and statistics, each student will be required to take at least four of the following courses:

 STA 5106-7 Computational Methods in Statistics I . II
 STA 5168 Statistics in Applications III
 STA 5169 Advanced Applied Statistics
 STA 5179 Survival Analysis
 STA 5225 Sample surveys
 STA 5238 Applied Logistic Regression
 STA 5507 Applied Nonparametric Statistics
 STA 5666 Statistics for Quality and Productivity
 STA 5676 Reliability Theory and Life Testing
 STA 5707 Applied Multivariate Analysis
 STA 5856 Time Series and Forecasting Methods
 STA 6174 Advanced Methods is Epidemiology

Required Health Sciences Seminar.  All students will be required to take a pass/fail seminar offered as part of a new degree in Interdisciplinary Health Sciences when that program is approved (the following description is taken from the approved proposal for that program)

 IHS 5XXX Health Sciences Seminar (1 credit hour, S/U, Fall, Spring).  A seminar series offered every semester in which FSU College of Medicine faculty as well as internationally recognized scientists present research from their laboratories and / or fields.  This seminar series will give all graduates of the IHS program a common language in medicine to use in their chosen field of work with topics of broad interest in areas such as human structure and function, the aging human, medical practice, the art of medicine, epidemiology and biostatistics, medical genetics and genomics, prevention of disease, chronic diseases, and health policy.

Elective Courses.  Elective courses may be taken in statistics or in other areas relevant to the student.s career goals.  Any courses taken to meet this requirement will be accepted when approved by the advisor.  The following are some examples of interdisciplinary possibilities:

 EPI 5XXX  Foundations of Epidemiology (3 credits).  A review of the basic underlying theoretical and statistical concepts used in epidemiology. Emphasis is placed on the practical and theoretical linkages between theoretical concepts and their statistical measurement.

 DEM 5135  Techniques of Demographic Methods (3 credits).  This course covers techniques of demographic data collection and evaluation as well as measurement of population processes, composition, and distribution, and social and economic characteristics of population.

 GEO 5159 Geographic Information Processing and Systems (3 credits).  A hands-on course on GIS topics, including locational control, spatial data structures, spatial cartographic statistics, modeling and analysis, trends in decision support, sensors, and geographic methods.

 BSC 5936C An Introduction to Bioinformatics  (3 credit hours).  This course introduces the emerging topic of bioinformatics. It is designed primarily for life science students who do not have an extensive background in mathematics, statistics, or computer science but who are interested in survey-level knowledge of bioinformatics and its techniques. The course is also suitable for students in mathematics, computer science, or statistics who wish to learn how methods drawn from their discipline are applied as bioinformatics. It is a 'hands on,' 'how to' lecture, demonstration, and laboratory (optional) course that includes both sequence- and structure-based methods.

 MAT 5932 Computational Biology  (3 credit hours).  The primary objective of this course is to introduce some of the numerical algorithms that are used in the simulation and analysis of models of biological systems.  The course focuses on both the algorithms and the implementation of algorithms in the C programming language.  Biological applications are discussed.  Some of the topics discussed are:  numerical optimization, numerical solutions of ordinary and partial differential equations, phase plane and bifurcation analysis, discrete dynamical systems, Monte Carlo methods and stochasticity.

A typical course program for a student who has not previously taken any of the required courses follows:
 
 
 

FALL	SPRING	FALL	SPRING
STA 5172   (3)	STA 5167   (3)	IHS5XXX   (1)	Electives     (9)
STA 5326   (3)	STA 5325   (3)	Electives     (6)	IHS5XXX   (1)
STA 5166   (3)	STA 5938   (3)	STA 5244   (3)