Ⅰ. Discipline Introduction
The predecessor of the Department of Statistics was a program in statistics in the 1970s that was joined by older generations of experts from the former National Bureau of Statistics, the State Planning Commission, and Renmin University of China. It was later renamed as Statistics, Economic Statistics. In 2019,it was selected as the first batch of national first-class undergraduate major construction point. So far, more than 40 graduates and more than 2,000 graduates have been trained for the country. A large number of graduates have become leaders at all levels, experts and scholars or business backbones, and have had important influences in all sectors of society, such as Han Baojiang, director of the Economics Department of the Party School of the Central Committee of CPC, Guo Hongbo, former director of the Hebei Provincial Bureau of Statistics, and Liu Ganghai, the former Captain of Hebei Investigation Team of the National Bureau of Statistics, Zhang Jiliang, Tian Yan, current deputy directors of Hebei Provincial Statistics Bureau, etc.
The Department of Statistics was established as a key discipline of Hebei University in 1996, and was rated as a provincial key discipline in 2005. In 1998, it had the right to grant a master's degree in statistics, and in 2010 it had statistics master section of first-level discipline. Currently, based on undergraduate majors in economic statistics, 3 academic master's degrees in statistics, quantitative economics, and national economics, 1 professional master's degree in applied statistics,and the first-level discipline doctoral section of applied economics in “Data and Economic Statistics Application” direction.
In recent years, we have continuously improved the economic statistics training system and improved the quality of talent training through a series of measures. Specifically:
(1) Strengthen professional teaching practice and further in-depth cooperation with government statistics departments. Statistics is a practical tool. In order to improve the teaching effect, in the process of revising the training program and the syllabus, increase the links of case teaching mode and experimental courses. On the other hand, make full use of the good relationship between our school and the government statistics department to further strengthen the construction of internship and practice bases.
(2) Strengthen the application of big data methods and advance the cutting-edge of teaching content. In response to the needs of talents in the new era, the Department of Statistics has further enriched and improved the big data curriculum system and strengthened the teaching of big data tools such as Python in the process of revising the talent training program and the syllabus. At the same time, we will strive for financial support to further strengthen the construction of the software and hardware conditions of the big data processing platform.
(3) Promote the cultivation of talents through scientific research and provide a better extracurricular environment for students’ development.
Pay attention to cultivating students' innovative ability. Guide students to participate in teachers' scientific research tasks, learn relevant content in academic practice, increase practical experience, and promote innovation and application capabilities. At the same time, extracurricular academic lectures are added to encourage students to participate in academic practice such as academic competitions.
Ⅱ. The Core Curriculum of the Discipline
Core Curricula of this major: statistics, national economics, multivariate statistical analysis, time series analysis, statistical forecasting and decision-making, non-parametric statistics, data mining and machine learning, sampling technology, national economic statistics, business management statistics, market survey and forecasting, etc.
Ⅲ. The Development Prospects of the Discipline
Statistics is science and art of collecting and analyzing data. Today, the world has entered the era of big data. Through the analysis of data, statistics has penetrated into all fields of social economy. Nobel Prize winner Thomas Sargent and HUAWEI founder and CEO Ren Zhengfei both proposed that “artificial intelligence is actually statistics.” So, the future society will inevitably have a wider demand for statistics talents.
Ⅳ. The Ability Requirements for Students Before Admission
(1) Students are required to have a solid foundation in mathematics, and have strong scientific and logical thinking abilities.
(2) Students are required to have a good foundation in foreign languages and at the same time master certain knowledge of computing software and hardware.
Ⅴ. Discipline Training Goals and Abilities Required for Graduation
This major mainly cultivates senior professionals who have a solid foundation in statistics and economics, are proficient in the application of modern statistical analysis methods and computer tools, and can be engaged in statistical information processing and data analysis in various social and economic sectors.
Training requirements: students should have a solid foundation in mathematics, statistics and economics, have the preliminary ability to apply statistical theory to analyze and solve practical problems in the social economy; have a high level of computer application, be proficient in commonly used statistical analysis software; be proficient in one foreign language, with certain capabilities of information acquisition and processing, such as foreign language data query, retrieval and so on.
Ⅵ. Employment Direction and Career Development Prospects
Graduates of this major can engage in statistical information processing and data analysis in government statistical agencies, various enterprises and institutions, and engage in related teaching and research works in teaching and scientific research institutions. The year-end employment rate of undergraduates in this major is over 98%, and the enrollment rate of postgraduate is over 30%.
Among the class of 2019, the proportions of enrollment and employment are 53% and 47% respectively. The employment destinations are financial institutions, government agencies, state-owned large and medium-sized enterprises, and foreign-funded enterprises; the enrollment destinations include many well-known universities at home and abroad, such as the University of Leeds in the United Kingdom, National University of Ireland Galway, Central University of Finance and Economics, Minzu University of China, University of International Business and Economics, etc.
