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Part time September MSc Three years
Biological Sciences (4) Computer Science (8)

FindAMasters summary

Are you fascinated by the world of statistics and its applications in the natural and social sciences? Look no further than our part-time MSc in Applied Statistics (Biostatistics) programme. Delve into the exciting field of biostatistics and learn how to apply statistical principles to study issues in medicine and biology. With a curriculum designed to meet societal and commercial needs, you'll gain a solid theoretical foundation and practical skills. Plus, our international academic team and strategic partnerships with renowned biomedicine companies provide extensive internship opportunities. Join us and become a statistical strategist in the next generation of pharmaceutics. Entry requirements vary, so check our website for details.

About the course

Applied Statistics (Biostatistics) is an important branch of statistics that concerns the use of statistical principles and methodologies to study issues and phenomena emerging in the fields of the natural and social sciences in order to infer and extrapolate from natural objects of interest . This discipline utilizes applications of mathematical statistical probability theory, methodology, and computational methods investigate, control, and explain, and analyze biometric data in order to break new grounds in medicine and biology.

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Entry Requirements

CHINA

Top 100 of 2021 Shanghai Ranking or World-class universities or First-class disciplines (MoE, People’s Republic of China): 75 percent or above (Weighted Average Mark)

Other universities: 80 - 85 percent or above (Weighted Average Mark), depending on your undergraduate institution

Note: Shanghai Ranking of The Best Chinese Universities is subject to annual update at View Website

UK:

UK upper second class honours (2:1) or equivalent

NORTH AMERICA:

3.0 Cumulative GPA (out of 4) or

3.2 Cumulative GPA in the final two years of your undergraduate programme


 Course Content

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Where is Xi’an Jiaotong-Liverpool University
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