Practical Training in Statistics

0 units

The Master of Arts in Statistics program at Department of Statistics and Data Science, Washington University in St. Louis, requires students to participate in extensive practical training as an essential component of the degree program. The program requires all full-time students to participate in practical training at least for one semester or summer session during their degree study. This requirement should be completed prior to the last semester in the degree program. The requirement does not require registration for additional credit but does require registration by ALL students, regardless of citizenship or visa status, for the zero-credit practical training course SDS 5910 for one semester or summer session in which a student participates in an internship or co-op. Practical training can be fulfilled by any one of the following three methods: 1. An off-campus internship or co-op position with an employer in the data science industry or data science related department of a company is strongly recommended as the most preferred component of the Practical Training. The position should be related to the Statistics curriculum and span at least four weeks in duration. The student is required to submit a written report after the internship ends. 2. On-campus research, or research project participation, where the research or project is related to data science under the sponsorship of one or more of a data science institution, industry practitioner or faculty member of Washington University in St. Louis. A detailed written report on the research or project participation should be submitted and approved by a faculty member in the Department of Statistics and Data Science. 3. Participation in the colloquium or statistics seminar in the Department of Statistics and Data Science, or other data science related research colloquium and seminar talks at Washington University in St. Louis. Students must attend talks regularly. A written report should be submitted to summarize the problems, ideas, approaches and results learned from at least four talks, and provide additional information from further reading and research of the topic.