Why Study Biometrics and Clinical Trials Operations
The Department of Mathematics and Statistics offers several related undergraduate and master’s level programs, including actuarial science, statistics, data science, predictive analytics, and mathematical finance. This certificate program, as well as our other certificate programs and master’s degrees, may be completed entirely online or face-to-face.
The certificate in biometrics and clinical trials operations prepares students for data analysis careers in the pharmaceutical and biotechnology industries. Students learn common techniques for designing and analyzing experiments for clinical trials, how to obtain regulatory and institutional review board approvals, as well as data mining and predictive modeling techniques for decision making. This twelve-hour graduate certificate can be earned in as little as two semesters. The career outlook for these individuals is very favorable.
The certificate in biometrics and clinical trials operations is designed for professionals with bachelor's degrees, but who would like to earn graduate credentials while without completing a master’s degree. All courses comprising this certificate count toward the master’s in predictive analytics: students who complete this certificate may then complete the entire MS degree after five additional courses.
The program faculty members are seasoned graduate-level professors of mathematics and statistics. They combine theory with real-life industrial applications, providing quality learning experiences. All full-time faculty members hold terminal degrees in mathematical or statistical fields, and part-time faculty members have many years of industrial experience. Many faculty members are engaged in multi-disciplinary research and are active in local, state, or national professional mathematics or statistics organizations.
Admissions Requirements
For information related to admission requirements or to view the courses within each program, please visit the graduate bulletin.
What Will I Learn
- demonstrate understanding of experimental designs for clinical trials.
- demonstrate data mining and predictive modeling techniques.
- are trained on current statistical and data science software, including R, Python, and SAS.
- can clearly communicate findings in written and oral reports.