国际学生入学条件
B.A., B.S., M.A., or M.S. in mathematics, statistics, or a closely related field.TOEFL Internet-Based Test (IBT) 79 or greater, TOEFL Paper-Based Test (PBT) 550 or greater score. IELTS of 6.5 or greater. Official transcripts from all institutions attended. All international transcripts must be recorded in English or officially translated to English.Students who have not taken mathematical statistics courses at the undergraduate level may be required to complete the equivalent courses in the appropriate background areas before taking graduate courses. A cumulative grade point average of 3.3 or higher in the last 60 hours of coursework.
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雅思考试总分
6.5
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雅思考试指南
- 雅思总分:6.5
- 托福网考总分:79
- 托福笔试总分:550
- 其他语言考试:NA
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申请截止日期: 请与IDP顾问联系以获取详细信息。
课程简介
博士 应用统计学课程设在德克萨斯州大学圣安东尼奥分校商学院管理科学与统计系,该课程借鉴了圣安东尼奥UT健康科学中心广泛的健康相关专业知识,以补充UTSA统计系。该计划将满足在生物统计学,商业,工程学和一般应用统计学领域接受博士学位培训的个人对国家和州日益增长的需求。统计方法无处不在,并在社会,物理和生物医学以及商业领域中用于处理信息以辅助决策。在这个先进的技术时代,对具有设计经验和通过最新的计算技术分析大型复杂数据集的专业知识的个人的需求在不断增长。特别是,真正需要具有博士学位的专业人员。应用统计学学位。
The Ph.D. program in Applied Statistics is housed in the Department of Management Science and Statistics in the College of Business at The University of Texas at San Antonio and draws on the extensive health-related expertise of faculty from the UT Health Science Center at San Antonio to complement the UTSA statistics faculty. The program will address growing national and state demands for individuals with doctoral training in the areas of biostatistics, business, engineering, and general applied statistics. Statistical methods are ubiquitous and used in the social, physical, and biomedical sciences and in business to process information to assist decision making. In this age of advanced technology, there is an increasing demand for individuals with the expertise in designing experiments and analyzing large complex data sets via the latest advances in computing. In particular, there is a real need for professionals with a Ph.D. degree in Applied Statistics. Statisticians are in very high demand in the fields of biostatistics and bioinformatics, business analytics and economics, engineering and industry, large data set processing and mining, and social and behavioral sciences.
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