Biostatistics

Website: https://medicine.utah.edu/dfpm/public-health/education/degrees/mstat-biostatistics

375 Chipeta Way, Ste A
Salt Lake City, UT 84108

Phone: 801-587-3315

The Master of Statistics program is an interdepartmental, interdisciplinary program at the University of Utah. Begun in 1976, this is arguably the oldest program of its kind still on campus. The program awards an MStat, which is a professional, non-thesis degree in statistics. It is administered by the University Statistics Committee, by agreement with the chairs of participating departments. Current tracks (participating departments) are biostatistics (Family and Preventive Medicine), econometrics (Economics), educational psychology, mathematic and sociology. Graduates of the Master of Statistics program have gone on to doctoral study and faculty roles at this and other universities, positions such as vice-presidents of health care corporations and pharmaceutical company leadership, as well as roles as statistical analysts and consultants at this university and elsewhere. The MStat in Biostatistics is housed within the Division of Public Health at the Department of Family and Preventive Medicine in the School of Medicine. The goal of this track is to provide the student with a good foundation in the basics of applied statistics, the fundamentals of numerous problems in the areas of health, an ability to apply statistical knowledge to health-related data, an ability to understand the problems and deal with the personalities of health care personnel and an ability to use computers to good advantage. For well-prepared students, this is a two and a half year program. Students with less preparation will need to extend their time in the program. In addition many MStat students are part-time, as they also have a full-time job or family responsibilities. As a track in an interdepartmental program, the track leadership is rotated among track faculty, approximately annually. There is a biostatistics director in the Division of Public Health, who assists coordination between the public health programs and the biostatistics track. Graduates of the biostatistics track of the MStat program are prepared to assume biostatistical consulting positions in which study design, project management and data analysis and reporting skills are required. Typically, these include state and local public health organizations, health care delivery systems, universities and medical schools, governmental health agencies and the pharmaceutical industry. The track's graduates have pursued careers in the pharmaceutical and health care industries, as well as going on to PhD programs. While applications from students with varied backgrounds will be considered, the MStat-Biostatistics is primarily intended to enhance the skills and career development of those with a bachelor's in mathematics, statistics or a related field, with coursework in calculus, statistics, programming, matrix algebra and biology.

• Bachelor degree from an accredited college or university with at least a cumulative 3.0 GPA.

• For International students only - TOEFL (minimum score of iBT 80 or pBT 550 or an IELT score of at least 6.5 submitted directly to University of Utah)

• Submit an application through Apply Yourself (AY) https://app.applyyourself.com/AYApplicantLogin/fl_ApplicantLogin.asp?id=utahgrad

• All unofficial transcripts must be uploaded (even if the University of Utah already has them and even if you attended the U) Send official transcripts directly to the University of Utah admissions office.

• Three (3) letters of recommendation - There is no specific format for recommendation letters

• Statement of purpose/Personal Statement - not to exceed 1000 words

• Current Resume or Curriculum Vitae (CV)

Prerequisites: Students are expected to have completed the following courses at the undergraduate level. A grade of B- or better is required in all prerequisite courses.

• Two semesters of calculus (Calculus I and II)

• Two semesters of biology

• Two semesters of statistics (applied or theoretical)

• Knowledge of matrix algebra (e.g., Math 2270)

• Knowledge of programming language (A real programming language, not statistical software or database)

• Evidence of multivariate calculus