1, calculus (from the definition of limit to multiple integrals).

2. Probability theory (discontinuous and continuous probability models, various density functions, probability functions, Bayesian priors, etc. ).

3, mathematical statistics (law of large numbers, central limit theorem, various statistical indicators, expectations, variance, etc. And statistical models. )

4, linear algebra (determinant, matrix, matrix application)

5. Real variable function, functional analysis, stochastic process, game theory, and necessary learning such as C++/Matlab or other programming tools. In addition, for empirical analysis, it is best to master one of R languages such as SPSS and SAS or statistical analysis programs.