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Teaching Research and Experience of Applied Statistics

编辑: 毕业论文 Release time: 2016-08-29 Editor: Graduation Thesis


Abstract: Applied statistics is a basic course for non-statistical majors such as management science and engineering, computer applications and communication technology in universities. The research issues, processed data, and deep information to be mined are very different for different majors, so the amount and degree of teaching content are very different. The author combines teaching research and practice, from teaching content, teaching methods, and The teaching experience of applied statistics in management science and engineering disciplines of non-statistics majors is expounded in terms of methods, innovative experiments, and so on.

Paper Keywords: Applied Statistics; Management Science and Engineering; Teaching Experience

Applied statistics is a highly applicable methodological science formed in solving economic and management problems. Its production and development are always closely related to reality. Through the study of this course, you can master the basics commonly used in economic management. Statistical principles and methods, familiar with statistical calculation methods and formulas, and able to correctly interpret calculation results, have the ability to apply quantitative statistical models and scientific statistical analysis methods for modern management and decision-making. Cultivating talents is the school's fundamental task and cultivating innovation Talents are an urgent requirement of the state for higher education institutions. Higher education institutions must realize the transformation from traditional knowledge to innovative training goals. The teaching goals of the curriculum have also been changed from previous unilateral teaching of teachers to training students to use knowledge and solve problems In order to improve students' ability in this area, the author has made some teaching innovations in teaching content, teaching methods and methods, and innovative experiments in the teaching of applied statistics in recent years to achieve this goal.

1. Innovation of teaching content system

Management science and engineering belongs to the first-level disciplines of management science (there is no second-level disciplines). It uses the theoretical methods of systems science and systems engineering as the main tools to study the general laws and special performance of management systems and economic systems. It is systems science , Management science, economics, operations research, engineering theory, leadership science, and many other different disciplines intersect, merge, and infiltrate into a new and emerging interdisciplinary discipline. Its goal is to cultivate management that can be managed at various levels of enterprises and governments at all levels. Senior management personnel working in departments, scientific research institutions and universities. The basic principles of management science and engineering teaching are: the basic theory is applied for the purpose. Reflected in the study of this course, the teaching content should be designed around the two main lines of theoretical knowledge application ability and quality training to design students' knowledge, ability and quality structure.

Choose the teaching content from the teaching goals and grasp the theoretical degree. Unlike the teaching content of statistics majors, the mathematical proof of statistical methods is not the main content of teaching. The teaching goal is to enable students to master Commonly used basic statistical principles, basic analysis methods, and methods of designing statistical mathematical models, training students to dig deep information through scientific statistical analysis methods, and cultivate students' rigorous scientific attitude and thinking mode. Therefore, we have highlighted the choice of teaching content The application of basic theory, basic analysis methods and knowledge, rather than the tedious statistical method mathematical proof process, focus on the analysis and application of statistical methods. For example, when teaching the central limit theorem, the first point should make students pay attention to the establishment of the central limit theorem. Prerequisites: All random variables are independent of each other, obey the same distribution, and have the same expectations and variances. It is emphasized that these random variables do not require compliance with the normal distribution, and other distributions such as exponential distribution and Bernoulli distribution. Applicable. The second point worth noting is that because when random When the number of variables n is large, the standardized random variable can approximately obey the standard normal distribution, so the type of problem that the central limit theorem can solve is: the number of known random variables to find the probability in a certain interval, or the known probability Lower limit to find the minimum number of these random variables, etc. After clearing the above two points, students are required to analyze the prerequisites of the theorem for all specific problems when they are specific, and then see if the solution of the problem can be transformed and summarized into the above problem types. In the process of teaching the central limit theorem, the teaching of the basic theory of the central limit theorem, the analysis of the problem, and the application of the central limit theorem are emphasized, and the proof and reasoning process of the central limit theorem does not require all students to thoroughly understand.

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