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MIT金融
SUGGESTED MATHEMATICAL BACKGROUND AND SKILLS
Listed below is an outline of the mathematical background that is desirable to have in order to be successful in the most challenging of courses in the program.
线性代数Linear algebra: Basic topics, including: matrix/vector notation, operations on matrices and vectors, determinants, elgenvalues and eigenvectors,quadratic forms, and systems of linear equations.
微积分Calculus: Multivariable differentiation and integration, series expansions, and function approximation and maximization.
概率论Probability: Sample spaces and random variables, common distributions and densities, moments of distributions, conditional probability and Bayes' theorem, law of large numbers, central limit theorem, joint distributions,covariance, correlation, and stochastic independence.
随机过程Stochastic processes: Random walks, Bernoulli trials,Markov processes, basic properties of linear time series models, continuous-time processes, and Ito's lemma.
统计学/计量经济学Statistics/econometrics: Parameter estimation, confidence intervals,hypothesis tests, linear regression models, ordinary least squares, and likelihood principle.
计算机编程Computer literacy: Basic programming experience and readiness to leam new tools and features; for example, familiarity with programming in MATLAB, Python, Java, or C++.Basic experlence with Microsoft Office business tools, especially use of Excel for data analysis and presentation.
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