《应用回归分析》是应用统计专业的核心专业课,因此既要保证专业知识输入,也须注重职业素养、政治素养。线上 + 线下的混合式教学能够给学生更多的学习自主性,也给线下课堂留了更多的时间,使得线下教学时可以安排更多的讨论,有助于知识延伸,同时亦有助于提升思政在教学设计中的占比。本文通过理论教学和案例教学的例子详细的评述如何实现两者的有效组合,放大优点,全面育人。“Applied Regression Analysis” is the core professional course of the applied statistics major. It is necessary to ensure the learning of professional knowledge, but also to pay attention to professional quality and political literacy. The combination of online and offline teaching can give students more autonomy in learning and leave more time for offline classes, so that more discussions can be arranged during offline teaching, which helps to extend knowledge and improve the proportion of ideological and political thinking in teaching design. In this paper, the examples of theoretical teaching and case teaching are discussed in detail how to realize the effective combination of the two, amplify the advantages and educate people comprehensively.
在大数据时代背景下的复杂数据需要更加高级的统计方法,《统计计算》这门课程从两个方面提升统计专业学生专业能力:(1) 把理论的统计方法通过编程变成可靠、高效的算法。(2) 借助现代计算机的处理能力,发展新的统计方法。因此,这是一门对编程能力要求更高的课程。针对应用统计系专业学生编程能力薄弱,采用案例演示教学法,充分把控理论方法和实践教学的难度和深度,因材施教,使学生不仅能够应用统计方法解决实际问题,也能理解背后的理论原理。In the era of big data, more advanced statistical methods are required to deal with complex data. “Statistical Computing” is a course to improve the professional ability of statistical students from two aspects: (1) The theoretical statistical methods are implemented into reliable, efficient computational algorithm. (2) Develop new statistical methods with the help of the processing power of modern computers. Therefore, this is a course that requires more programming ability. Since the programming ability of students majoring in Applied Statistics is weak, the case demonstration teaching method is introduced in the Statistical Computing course to balance between the theoretical and practical difficulty and depth. Thus, students will not only be able to apply statistical methods to solve practical problems, but also understand the theoretical principles behind them.
《时间序列分析》是高等院校应用统计学专业的核心课程,也是数学与应用数学,经济学,数据科学与大数据技术等专业的选修课程。文章深入剖析了《时间序列分析》课程在教学过程中遇到的若干挑战,并从课程思政、教学内容优化及教学模式创新等多个维度展开细致探讨。“Time Series Analysis” is a core course for applied statistics majors in universities, and an elective course for majors such as mathematics, economics, and data science. This article delves into several challenges encountered in the teaching process of “Time Series Analysis” course, and conducts detailed discussions from multiple aspects, including curriculum ideological and political, improvement of teaching content, and innovation in teaching modes.
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