First, the professional definition

Applied statistics mainly studies the basic theories and methods of statistics, and can skillfully use computers to process and analyze a large number of data and solve practical problems in various fields. It mainly involves data analysis, data management, statistical investigation and so on.

Second, the curriculum system

Advanced mathematics, linear algebra, probability theory and mathematical statistics, introduction to statistics, multivariate statistical analysis, statistical modeling and R software, regression analysis, time series analysis, econometrics, data mining, python and data analysis, database technology, programming foundation, etc.

Third, the development prospects and employment direction

Financial and consulting enterprises: data analysis, social investigation, risk management, actuaries; All kinds of enterprises: statistical investigation, statistical information management and quantitative analysis.

Fourth, the direction of postgraduate entrance examination

Statistics, applied statistics, accounting, probability theory and mathematical statistics.

Five, applied statistics professional courses

Mathematics: mathematical analysis, advanced algebra, analytic geometry, real variable function and functional analysis, probability theory, optimization theory and method.

Statistics: mathematical statistics, sampling survey, applied regression analysis, multivariate statistical analysis, time series analysis, nonparametric statistics, applied stochastic process, statistical calculation and application software, statistical optimization in big data.

Computer class: data structure and algorithm design, parallel computing and software design, data mining, database principle, machine learning and its application, artificial intelligence.

Finance: microeconomics, econometrics, financial mathematics, financial modeling and program analysis, financial engineering, quantitative investment.

Experiments and practice: introduction to computational thinking experiment, college physics experiment, data structure and algorithm design course design, data mining course design, machine learning and its application course design, applied regression analysis course experiment, multivariate statistical analysis course experiment, time series analysis course experiment, statistical calculation and application software course experiment, engineering training, enterprise practice (financial big data analysis, software development and algorithm design).