Applied Statistics, M.S.
Norman, USA
MSc
DURATION
LANGUAGES
English
PACE
Full time
APPLICATION DEADLINE
EARLIEST START DATE
Sep 2026
STUDY FORMAT
On-Campus
Key Summary
About: The Master of Science in Applied Statistics at The University of Oklahoma trains students in statistical methods, probability, data analysis, and statistical programming using R and SAS. It emphasizes applying theory to real-world problems through coursework, specialized electives, research projects, and internships. The flexible curriculum helps students balance study with other commitments and build practical skills in modeling, interpretation, and communication for health, finance, government, and industry. Keywords: applied statistics, statistical analysis, data science, biostatistics, analytics.
Career Outcomes: Graduates find roles as data analyst, statistician, biostatistician, data scientist, analytics consultant, research associate in public health, finance, government, and industry.
The Master of Science in Applied Statistics program is designed to give students practical skills for analyzing and interpreting data across various fields. It covers core topics like statistical methods, probability, and data analysis techniques, helping students build a strong foundation. The program also includes coursework in statistical programming and software, so students become comfortable using tools like R and SAS, which are essential in today’s data-driven world. Through their studies, students learn how to turn complex data into meaningful insights, preparing them for roles in industries such as health, finance, or government.
The program emphasizes applying statistical theories to real-world problems, with opportunities for hands-on experience. Students can choose from specialized courses and may participate in research projects or internships, gaining practical exposure. The curriculum is designed to be flexible, allowing students to balance their studies with other commitments. Overall, it aims to equip students with the knowledge and skills needed to analyze data effectively and make informed decisions in their careers. The focus remains on practicality and relevance, ensuring graduates are prepared for diverse career paths in applied statistics.
