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Masters Degrees in Statistics, USA

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The Department of Mathematical Sciences offers a professionally oriented Master’s of Arts degree program in applied statistics. The lively and versatile curriculum focuses on training that is applicable in the real world, and the program aims to prepare skillful statisticians for professional careers in industry. Read more
The Department of Mathematical Sciences offers a professionally oriented Master’s of Arts degree program in applied statistics. The lively and versatile curriculum focuses on training that is applicable in the real world, and the program aims to prepare skillful statisticians for professional careers in industry. The track includes an integral lab component that emphasizes the practice of contemporary data analysis and exposes students to methods, software and theory commonly used in applications of statistics.

The MA is designed to provide students with a solid foundation of practical knowledge to work with applied statistics in depth, for future careers in the public and private sectors as statistical scientists, consultants and engineers to manage and analyze data. The program requires courses specific to the area of applied statistics, and the student is required to finish 10 courses and two 1-credit capstone seminars for a total of 42 credits. An exit exam or final thesis is not required.

Driven by the ever-greater reliance of businesses and governments on data, the demand for professionals with strong quantitative analytical skills is now higher than ever. Program graduates will be trained to pursue careers in a variety of fields that require data-crunching and quantitative analysis. Well-trained statisticians and data scientists are employed in the following roles in a wide spectrum of industries:
◾statistical consultants
◾risk managers
◾insurance actuaries
◾quants (and traders)
◾production/manufacturing quality control managers
◾market researchers
◾sports statisticians
◾economists
◾biomedical, biometrics, and bioinformatics researchers
◾sociology researchers
◾psychology researchers
◾biostatisticians in pharmaceutical industry
◾government statisticians (census)

All applicants must submit the following:

- Online graduate degree application and application fee
- Transcripts from each college/university which you attended
- Three letters of recommendation
- Personal statement (2-3 pages) describing your reasons for pursuing graduate study, your career aspirations, your special interests within your field, and any unusual features of your background that might need explanation or be of interest to your program's admissions committee
- Resume or Curriculum Vitae (max. 2 pages)
- Official GRE scores

And, for international applicants:
- International Student Financial Statement form
- Official bank statement/proof of support
- Official TOEFL, IELTS, or PTE Academic scores

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Master of Business Statistics. SAN FRANCISCO. Hult is the world’s most international business school with campuses and rotation centres in Boston, San Francisco, London, Dubai, Shanghai, and New York. Read more
Master of Business Statistics
SAN FRANCISCO

Hult is the world’s most international business school with campuses and rotation centres in Boston, San Francisco, London, Dubai, Shanghai, and New York. With Hult’s Global Rotation program, students have the opportunity to select their home campus and then spend up to three months studying at two others.

Only Hult allows you to complete your Master while immersing yourself in up to three of the world’s most influential cities. The U.S. demand for scientific graduates means Master of Business Statistics students can receive up to a three-year U.S. working visa (OPT) post studies.

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USF’s one-year Master of Science in Analytics (MSAN) program delivers a rigorous curriculum focused on mathematical and computational techniques in the emerging field of data science. Read more
USF’s one-year Master of Science in Analytics (MSAN) program delivers a rigorous curriculum focused on mathematical and computational techniques in the emerging field of data science. The curriculum emphasizes the careful formulation of business problems, selecting effective analytical techniques to address those problems and communicating solutions in a clear and creative fashion.

98% of MSAN students are employed within three months of graduation at companies such as Google, Williams-Sonoma, Amazon, Capital One Labs, Eventbrite, and Mozilla.

A Technically Challenging Curriculum

The program's challenging curriculum features seven-week courses designed specifically for MSAN students — they're not offered in other programs or departments. Students master subjects from computer science, statistics, and management such as regression, web scraping, SQL and NoSQL database management, natural language processing, business communications, machine learning, cluster analysis, application development, and interviewing skills. Students primarily use programming languages like R and Python in their classes and learn how to effectively use distributed computing technology such as MapReduce, Hadoop, and Spark, and become intimately familiar with cloud technology such as Amazon Web Services.

Practicum Program

Practicum projects allow students to work an average of 15 hours per week for nine months tackling data science and analytics problems at companies around the San Francisco Bay Area and beyond. Past and current partners include Uber, Airbnb, Eventbrite, Google, Capital One Labs, AT&T Big Data, Zephyr Health, and the Houston Astros. Groups of two to four students - supervised by MSAN faculty - work on a data-driven business problem and produce a defined set of deliverables.

Faculty

Our faculty represent the fundamental multidisciplinary nature of the big data industry. They’re traditional academics and data scientists actively working in the field, using real industry experience to inspire their instruction. Their areas of expertise include deep learning, natural language processing, databases, statistical modeling, network analytics, algorithms, unsupervised learning, machine learning, optimization, health analytics and signal processing.

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