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Graduate School & Research Building (GSR)

Suite 2.210

Office Hours:

Monday - Friday
8 a.m. to 5 p.m.

Contact US:

Phone: (210) 458-4331

Fax: (210) 458-4332

Admissions Email: Graduate.Admissions@utsa.edu
Recruitment Email: GradRecruit@utsa.edu

Applied Statistics (Ph.D.)

Applications are only being accepted for the part-time Ph.D. in Applied Statistics program for Fall 2017. 

Basic Degree Information/Description

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.

Why an Applied Statistics Ph.D.?

  • The college's doctoral classes are diverse in terms of professional experience, academic experience, cultural influences, and international experiences.
  • Commitment to research and a passion for teaching are two of the qualities that distinguish both our doctoral faculty and our graduates.
  • Students work closely with faculty members in small classes, seminars, research projects, and other assignments, aimed toward developing the analytical skills competencies to conduct independent quality research.

Admission Requirements and Prerequisites

In addition to satisfying the University-wide graduate admission requirements, a B.A., B.S., M.A. or M.S. in mathematics, statistics, or a closely related field is required. 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. For more specific requirements, please visit the Online Graduate Catalog.  The admission requirements consist of:

Transcripts: Official transcripts from all institutions attended. All international transcripts must be recorded in English or officially translated to English.

Graduate School Application: Yes

Test Scores: General GRE Required, not older than five years.

Resume: Professional CV/Résumé listing prior experiences in the field of Applied Statistics. 

Letters of Recommendation: Three letters of recommendation are required from academic or professional sources familiar with the applicant’s background, attesting to the student’s academic and personal attributes for success in the program and potential for contributing substantially to a field of study related to the degree.

Statement of Purpose: Yes, a written personal statement/essay describing experiences, interests, and goals for pursuing the Ph.D. in Applied Statistics.

Minimum TOEFL/IELTS score (for International Applicants): International students must have a minimum score of 79 on the TOEFL Internet-based test, 550 on the TOEFL paper-based test, or 6.5 on the IELTS.

Additional Requirements: International students and those with international degrees may be required to submit additional documents per our admissions policies and procedures. The Graduate School reserves the right to request any additional documents needed to fairly and consistently evaluate applicant credentials.

Interview: Applicants may be asked to appear before the admissions committee for a personal interview. 

Career Options Available for a Ph.D. in Applied Statistics

  • Academia
  • Government
  • Private industry

Research Opportunities

Research is carried out while students are taking formal coursework and during the summers. As research assistants, students are involved with faculty in joint research activities and pursue their own research objectives under faculty supervision. These activities should lead to authoring or co-authoring papers presented at academic meetings and possibly submitted for publication by the time the student is ready for dissertation research. (To compete successfully in the job market, students should give high priority to presenting papers at meetings and publications while in the program.)

Contact Information

Graduate Advisor of Record: Ram Tripathi, Ph.D.
Email Address:Ram.Tripathi@utsa.edu
Telephone: (210) 458-5549

Degree Catalog Link:http://catalog.utsa.edu/graduate/business/managementsciencestatistics/#applied-statistics-phd

Degree Website: http://business.utsa.edu/phd/index.aspx

Funding Opportunities

Full-time students admitted to the Ph.D. program are usually awarded fellowships that include a waiver of tuition, a stipend to help cover living expenses, and some health care benefits. The stipend is likely to vary but could be in an amount up to $22,000 annually. These stipends carry with them the expectation that the student will work 20 hours a week in either a research or teaching assistantship.

Course Scheduling and Offerings

This program will admit full-time as well as part-time students. Full-time students will normally be expected to enroll for nine hours each long semester, and three hours in the summer semester while part time students are expected to enroll for a minimum of three credit hours each semester. Most courses will be offered during the evening. Ph.D. full-time students normally serve as either a teaching assistant or research assistant throughout the program. These experiences are an important part of the training and overall doctoral experience.