国际学生入学条件
he MS and the PhD in Statistics are awarded by the Graduate College. Instruction is offered through the College of Liberal Arts and Sciences. The MS is offered without a thesis. Please note the minimum requirements for Graduate program:
A U.S. bachelor's degree from a regionally accredited college or University, or an equivalent degree from another country as determined by the Office of Admissions.
A minimum grade-point average (GPA) of 3.00, or foreign equivalent as determined by the Office of Admissions, on the completed undergraduate degree or on at least 12 hours of a graduate degree.
The GRE is required, however, there is no set minimum GRE score. The subject test is not required. Your GRE scores must be reported directly from the testing agency. Those dated within the last five years are acceptable. The University of Iowa institution code is 6681 (you do not need department codes). Please not our department does not accept GMAT scores. We may request an interview (by telephone, Skype, or in person) prior to making an admission decision.
TOEFL iBT - Total score 81
TOEFL PBT - 550
IELTS - Overall score of 7 with no subscore less than 6
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IDP—雅思考试联合主办方

雅思考试总分
7.0
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雅思考试指南
- 雅思总分:7
- 托福网考总分:81
- 托福笔试总分:550
- 其他语言考试:DuoLingo (DET) - Score of 105+
CRICOS代码:
申请截止日期: 请与IDP顾问联系以获取详细信息。
课程简介
统计专业的哲学博士课程要求至少76学时的研究生学分,包括已完成MS学位的工作。研究生院要求拥有至少3.00的gpa才能获得博士学位。但是,统计学和精算学系要求获得至少3.40的gpa才能获得博士学位。在统计中。这包括用于满足学位要求的所有课程,以及与学生课程相关的其他课程。博士 学生完成必修课程,包括在四个集中领域之一中的四门课程:生物统计学,概率/数学统计,统计计算或精算科学/金融数学(有关领域描述和课程列表,请参见下面的“集中领域”)。他们可能会在其他部门参加课程工作或研讨会,以将专业领域与其他知识领
Graduates will be able to have a solid understanding of the mathematical and statistical theory that underlies statistical methods, conduct literature reviews to summarize the state of the art for specific theoretical and applied topics, formulate, implement, and assess appropriate statistical models for analyzing data, identify limitations of existing methods and independently develop and assess novel methods (e.g., for analyzing new types of data), appreciate the issues of uncertainty, reproducibility, and computability in data analysis, collaborate with non-statisticians to help collect and analyze data and acquire effective communication skills for disseminating statistical findings.
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