M.S. Degree Program
The M.S. program prepares students to function as biostatisticians or biostatistical consultants. Upon completion of the M.S. in biostatistics, the student has an extensive understanding of biostatistical theory and practice and is proficient in the computation and application of statistical methods to one or more areas in the health sciences.
M.S. Degree Requirements
The biostatistics M.S. program consists of 36 credit hours including collaborative research experience, annual evaluations, and the successful completion of the master's general examination.
The course plan consists of 27 credit hours from required biostatistics core courses including 3 credit hours of Collaborative Research Experience. This requirement ensures the completion of a research component through collaborative effort within or external to the department.
A minimum of 9 credit hours in elective courses is also required. Elective credit hours include a minimum of 3 and a maximum of 6 credit hours in approved courses from outside the department and a minimum of 3 and maximum of 6 credit hours in biostatistics electives. Biostatistics electives can be chosen from the list of elective classes and the required Ph.D. courses.
Required Biostatistics M.S. Core Courses (27 credit hours)
|BIOS 810 Clinical Trials||3|
|BIOS 820 Statistical Computing/SAS Base L1||3|
|BIOS 830 Experimental Design||3|
|BIOS 835 Categorical Data Analysis||3|
|BIOS 840 Linear Regression||3|
|BIOS 871 Mathematical Statistics
|BIOS 872 Mathematical Statistics II||3|
|BIOS 890 Linear Models||3|
|BIOS 898 Collaborative Research||3|
Students are evaluated each April by their graduate advisors and the director of the graduate program. These evaluations provide feedback to the student regarding the progress they are making in meeting program requirements, classroom performance, and research performance.
Master's General Examination
The master's general examination is given after a student’s third full semester in residence, assuming the completion of the following courses: Mathematical Statistics I and II, Statistical Computing, Experimental Design, Linear Regression, and Categorical Data Analysis. The examination has 3 purposes: to assess the student’s strengths and weaknesses; to determine whether the student should be awarded the M.S. degree; and, if it is a degree goal, to determine whether the student is prepared to continue into the Ph.D. program.