The MSc in Applied Statistics will aim to train you to solve real-world statistical problems. When completing the course you should be able to choose an appropriate statistical method to solve a given problem of data analysis and communicate your results clearly and succinctly. The course aims to equip you with the computational skills to carry through the analysis and answer the problem as presented.
The MSc is designed to provide a broad but high-level training in applied statistics, computational statistics and statistical methods. These topics are taught through mathematically demanding lectures and problems classes. There is extensive hands-on experience of analysis of real data through practical classes. There is also a dissertation on an applied project. You will have approximately three months to work on your dissertation under the supervision of an academic in the department. You will be assessed on your performance in written examinations around May, through your work in the assessed practicals set throughout the year, and by the quality and depth of your dissertation.
Core topics in the taught element of the course include statistical theory and methods, statistical computing, R programming, statistical data mining and machine learning, and advanced simulation. There are in addition a number of standard and advanced options in topics which vary from year to year. In recent years these have included survival analysis, stochastic models in mathematical genetics and actuarial science.
University of Oxford, United Kingdom
The MSc in Applied Statistics will aim to train you to solve real-world statistical problems. When completing the course you should be able to choose an appropriate statistical method to solve a given problem of data analysis and communicate your results clearly and succinctly. The course aims to equip you with the computational skills to carry through the analysis and answer the problem as presented.
The MSc is designed to provide a broad but high-level training in applied statistics, computational statistics and statistical methods. These topics are taught through mathematically demanding lectures and problems classes. There is extensive hands-on experience of analysis of real data through practical classes. There is also a dissertation on an applied project. You will have approximately three months to work on your dissertation under the supervision of an academic in the department. You will be assessed on your performance in written examinations around May, through your work in the assessed practicals set throughout the year, and by the quality and depth of your dissertation.
Core topics in the taught element of the course include statistical theory and methods, statistical computing, R programming, statistical data mining and machine learning, and advanced simulation. There are in addition a number of standard and advanced options in topics which vary from year to year. In recent years these have included survival analysis, stochastic models in mathematical genetics and actuarial science.
University of Oxford, United Kingdom
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