The Financial Statistics stream of the MSc Statistics programme is mainly intended for students wishing to pursue careers in the finance industry or as a stepping stone towards PhD study in statistics for finance.
It provides high-level training in statistics with applications in finance. You will learn to analyse and critically interpret data, build statistical models of real situations, and use statistical software packages.
The compulsory courses consolidate your understanding of fundamental ideas in probability and statistics and introduce advanced topics. You...
The Financial Statistics stream of the MSc Statistics programme is mainly intended for students wishing to pursue careers in the finance industry or as a stepping stone towards PhD study in statistics for finance.<br/><br/>It provides high-level training in statistics with applications in finance. You will learn to analyse and critically interpret data, build statistical models of real situations, and use statistical software packages. <br/><br/>The compulsory courses consolidate your understanding of fundamental ideas in probability and statistics and introduce advanced topics. You can choose options to focus on various topics, including those in statistics (with applications in finance or social science), data science, or approved courses from other departments. <br/><br/>Graduates of the programme are awarded Graduate Statistician (GradStat) status by the Royal Statistical Society if a specific combination of modules is taken. <br/><br/>The research stream is similar to the MSc Statistics (Financial Statistics) nine-month programme but involves a compulsory dissertation which replaces one units worth of optional courses and extends the length of the programme to 12 months.
Some courses vary and have tailored teaching options, select a course option below.
Course Details
Information
Study Mode
Full-time
Duration
1 Years
Start Date
09/2025
Campus
London School of Economics and Political Science
Application deadline
Provider Details
Codes/info
Course Code
Unknown
Institution Code
L72
Points of Entry
Unknown
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