由于近年来国家对统计学相关人才需求的不断扩大，2010年，教育部批准设立应用统计专业硕士学位．应用统计专业硕士学位的设立，是为了避免学术型硕士培养中过于理论化，缺少实践，与实际工作不能有效衔接的情况．与国外相比，国内的应用统计专业起步较晚，例如，美国就很重视统计学科的发展，美国的院校很早就开展了应用统计专业硕士的教育．国内也有很多优秀的高校，比如，中国人民大学、北京大学等，在应用统计专业硕士的教育上都取得了不错的成绩．通过对比美国和国内统计学排名靠前的院校的应用统计专业硕士课程设置，可以看出北京师范大学统计学院在应用统计专业硕士的课程设计方面还有改进的余地． 　　本文首先调查了美国统计学专业官方排名前十名的学校以及与本校有交流合作的学校的培养方案和课程设置及其内容，同时研究以中国人民大学和北京大学为例的国内高校的培养方案和课程设置情况，进行总结对比，对美国高校的课程内容利用Python软件进行停用词过滤，并且进行分词处理，同时对词频进行统计，最后将所有词汇按照词频进行排序、画图，最终得到简洁直观的词云图进行分析．其次，本文选取2013-2017届应用统计研究生的毕业论文，提炼出每篇论文所运用的方法和模型，形成文本文件，通过Python软件，利用文本挖掘等方法进行文本分析，将所有方法和模型按照词频进行排序，对广泛运用的方法和模型进行总结．最后，本文对2015-2018届专硕班毕业生进行问卷调查，对北京师范大学统计学院现行的课程设置进行综合考量，即对于学院已经开设的课程，了解毕业生的正式工作与所学的课程的相关程度；对于覆盖内容不全以及学院未开设的课程，征集毕业生对于课程是否有必要开设的意见． 　　通过以上三个方面的调查对比研究，可以看出在课程的总体设置方面，对于统计学基础课程的设置覆盖得很全面，但是在选修课的多样性方面还具有不足之处，现有的课程方向性不明确，可以考虑借鉴其他学校的课程方向分类，结合我校的特点进行课程设置的改进．同时，可以增加院系之间的合作，鼓励学生跨专业选修课程．对于内容覆盖不全的课程，根据本文的研究，提出了具体的改革方案．

Recently, national demand for statistical talents continues to expand. In 2011, the master degree in applied statistics passed the approval of the Ministry of Education and was formally established.The establishment of the master's degree in applied statistics is to avoid the emergence of over-theoreticization, lack of practice, and ineffective convergence of practical work in the academic master training program.Compared with foreign countries, the domestic application statistics training program started relatively late. For example, the United States attaches great importance to the development of the statistics department. American colleges and universities have started education in applied statistics masterprogramvery early.There are also many outstanding universities in China, which have achievedalot in application statistics training program education.Comparing the professional master's degree programs in the top statistical universities, apparently there is still room for improvement in the curriculum design of our school. This article first investigated the training programs’ curriculum and its content of the top ten schools in the United States in Statistics field. At the same time, this article studied the training programs and curriculum settings of domestic collegesusingRenmin University of China and Peking University as examples. This article used Python software to filter words of curriculum’s content, and then access the word frequency, and at the same time, all the words are sorted and plotted according to word frequency, and finally achieved a simple and intuitive word cloud images for analysis. Secondly, this paper selected graduation thesis of 2013-2017 graduate students, extracted the methods and models used for each paper, and formed a text file.Through Python software, using text mining and other methods to analyze the text file, all methods and models were sorted according to word frequency, and the widely used methods and models were summarized.Finally, this paper conducted a questionnaire survey of 2015-2018 graduate students, in order to take a comprehensive consideration of the current curriculum settings of Beijing Normal University. Through the investigation and comparison of the above three aspects, in the overall setting of the course, it has covered most all the basic statistics courses. However, there are certain deficiencies in the diversity of elective courses.The directionality of the existing courses is not clear. We can consider the classification of otheruniversities’ curriculum and combine the characteristics of our school to improve the curriculum.At the same time, the cooperation between departments can be increased to encourage students to elective Cross-curricular elective courses.For the course of incomplete covered content, based on the study of this article, specific improvements are also proposed.