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Suggested Background Work and Self-Assessment
Suggested Mathematical Background
Listed below is an outline of mathematical background that we think is desirable to have in order to be successful in the most challenging of courses in the program.
Linear algebra: Basic topics, including: matrix/vector notation, operations on matrices and vectors, determinants, eigenvalues and eigenvectors, quadratic forms, systems of linear equations. At the level of Lang, Linear Algebra, 1987, 3rd Edn., Chapters 1-8.
Calculus: Multivariate differentiation and integration, function maximization. At the level of Larson and Edwards, Calculus, 2009, 9th Edn., Chapters 4, 13.
Probability: Law of large numbers, Central Limit Theorem, moments of distributions, conditional expectation and Bayes rule, commonly used distributions, multivariate distributions, independence. At the level of DeGroot and Schervish, Probability and Statistics, 2002, 3rd Edn., Chapters 1-5.
Statistics/Econometrics: Parameter estimation, confidence intervals, hypothesis tests, ordinary least squares, likelihood principle. At the level of DeGroot and Schervish, Probability and Statistics, 2002, 3rd Edn., Chapters 6-8, 10.
Computer literacy: Basic programming experience. We use Matlab, Java, C, Fortran, VB, etc. would provide sufficient foundation for quickly learning Matlab features.
To assess the adequacy of your mathematical background, please use the following self-assessment test. If you experience difficulties in any particular area, we strongly recommend that you strengthen your skills through self-study or formal coursework prior to enrolling in the MFin program.
Please consider the following resource should you require prep-work:
(1001HB, 4001HB) http://web.hbr.org/store/landing/courses/
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