Statistics for Clinical Trials MSc
Help further medical research as you learn how to use advanced statistical tools and data analysis techniques that enhance the precision, efficiency, and reliability of clinical trials. Learn flexibly and remotely from University College London.
Level
Masters DegreeDuration
1 Year Full-timeLanguage
EnglishTotal Tuition Fee
£17,300
Statistics for Clinical Trials MSc
Masters Degree (Postgraduate)
1 Year Full-time
Total tuition fee
£17,300
Unlock career opportunities in clinical research as a qualified statistician
The use of statistics in clinical trials is expanding amongst healthcare professionals, researchers, and data scientists. Having the right analytical and statistical skills will allow you to stand out in this competitive field.
Learn how to effectively design, conduct, and evaluate clinical research using advanced statistical methods with this online degree from University College London.
Explore clinical trial designs and trial phases
On this programme, you’ll gain expertise in designing robust clinical trials, including advanced trial designs, data interpretation, and systematic review methods.
Apply advanced statistical analysis techniques
Develop proficiency in statistical analysis, including foundational and advanced techniques crucial for accurate data interpretation in clinical trials.
This includes statistical inference, which allows you to draw accurate conclusions from clinical trial data, and meta-analysis, which combines results from multiple studies to assess overall evidence and draw robust conclusions.
Understand health economics
You’ll also delve into health economics, an essential aspect of assessing the cost-effectiveness of healthcare interventions within clinical trials.
Upskill in statistical coding software, R and Strata
Learn to code and analyse clinical trial data using leading statistical software tools like R and Stata.
These powerful programs will enable you to manage large datasets, perform complex statistical analyses, and create reproducible research workflows, making you a valuable asset in any clinical research team.
Become a statistician with the experts at UCL
In joining this degree, you’ll learn from the expertise of UCL's world-renowned faculty, who bring a wealth of applied experience and theoretical knowledge in clinical trials, statistics, and health research.
Throughout the course, you’ll utilise real trial examples and the latest methodological developments in clinical trial statistics based on UCL’s own publications.
What career opportunities will this degree unlock?
Clinical trials is an expanding and highly competitive field of research. Earning a qualification that specialises in the statistical analysis of clinical trials positions you as a highly skilled professional who can pursue any number of roles. Upon completing this degree, you’ll be well-positioned to land a job as a:
Statistician in Clinical Trials: Become an integral part of research teams, contributing to the design, analysis, and interpretation of clinical trial data.
Biostatistician: Work in academic institutions, healthcare organisations, or pharmaceutical companies, analysing biomedical data to inform research and decision-making.
Academic Researcher: Pursue a career in academia, conducting research in clinical trials methodology, biostatistics, or related fields, and contributing to advancements in the field.
Is this a part-time or full-time degree?
The Statistics for Clinical Trials MSc offers full and part-time study options. This allows working professionals and those who are unable to attend on-campus classes to pursue the programme from anywhere in the world, over one, two or five years.
You can expect to devote approximately 20-25 hours per week for full-time study and around 10-12 hours per week for part-time study to meet the demands of the course.
The overall contact and self-directed study hours are 150 hours for a typical 15-credit module which includes approximately three hours of live online seminars per week.
Academic Qualifications:
Applicants to the Statistics for Clinical Trials MSc should hold a minimum of an upper second-class Bachelor's degree from a UK university or an equivalent qualification from overseas in a related quantitative discipline such as mathematics, statistics, biostatistics, genetics, or computational biology.
Clinicians and allied health professionals must possess a degree, such as an MBBS, and demonstrate completion of quantitative modules, along with a strong interest in medical statistics.
If you’re an international student, you can find country-specific information, including qualification equivalencies on UCL’s website directly.
Language Qualifications:
The English language level for this programme is: Level 2. If you’re an international student or English is not your native language, you’ll need to provide your knowledge of English by demonstrating an education that leads to an academic qualification or an English language qualification or test result.
UCL offers additional English language support through their Pre-Master's and Pre-sessional English courses, specifically designed for those interested in postgraduate study at UCL.
Master advanced clinical trial designs, data interpretation, and systematic review methods.
Gain foundational knowledge in trial design, patient allocation, and statistical analysis.
Apply health economic principles and analysis techniques within clinical trial contexts.
Perform meta-analyses using advanced statistical models and assess study heterogeneity.
Develop proficiency in R and Stata for coding and analysing clinical trial data.
Understand and apply key statistical models and hypothesis testing in clinical trials.
Explore complex trial designs, sample size calculations, and advanced statistical methods.
Conduct independent research and effectively communicate findings through a dissertation.
UCL (University College London)
UCL was founded in 1826. It was the first English university established after Oxford and Cambridge, and the first to open up university education to those previously excluded from it.