Sep 20, 2020  
2020-2021 Graduate Catalog 
    
2020-2021 Graduate Catalog

Statistics and Data Science, MS


College of Natural Sciences and Mathematics  > Department of Mathematics  > Statistics & Data Science, MS

The Master of Science in Statistics and Data Science, offered by the Department of Mathematics, provides students with training in the statistical analysis of data sets, as well as in state of the art data mining techniques. The program includes computational implementations on real data sets and learning key theoretical concepts. The program provides students with necessary skills required for professional positions in data analysis and statistics. Students will be equipped for employment in biomedical fields and health institutions, in oil and gas research and development, in financial and actuarial sectors, and related areas. Recent graduates from our U of H applied mathematics MS and PhD programs who acquired similar skills are currently employed in the banking, biomedical, energy, insurance and financial industries, or teach in high schools and community colleges.

For further information, please see the Master of Science in Statistics and Data Science page.

Admission Requirements


A complete graduate school application must be submitted along with any applicable fee. An MS applicant will have earned a bachelor’s or a master’s degree. Scores from the General GRE examination taken in the last 5 years are optional (verbal, quantitative, and analytical writing; advanced GRE is recommended but optional). For students who did not earn a prior degree from a U.S. institution or a country where English is the medium of instruction, (see list ) students must meet minimum test scores to demonstrate English language proficiency.

The admissions committee will evaluate the credentials of each applicant for the MS program, considering a broad range of criteria, including:

  1. the content of the undergraduate program and, if applicable, graduate programs and competency in mathematics,
    • Applicants must have a good background in mathematics (including calculus / advanced mathematics, and linear algebra)
  2. a cumulative GPA of 3.00 or better in the last 60 hours of course work,
  3. letters of recommendation from three (3) individuals (preferably faculty members), who are able to judge the candidate’s academic abilities and potential for scholarly research, and
  4. GRE scores, if submitted (see above).
  5. English language proficiency test scores, if applicable.

Additional notes:

  • A student needs not to have majored in mathematics to be admitted.
  • A background in probability and statistics is not essential but is a plus.
  • Proficiency in at least one of the main programming languages used in data analysis (R, SAS, Matlab, Python, etc) is not required but is helpful.

Degree Requirements


Credit hours required for this degree: 30.0

Elective Course Options


3.0 Credit Hours from the list below

Summer Research Project


3.0 Credit Hours

  • Credit Hours: 3.0
  •  

    Students successfully complete a summer research project in data analysis under the supervision of a faculty mentor.

    Within these requirements, students are encouraged to pursue their own interests. In particular, the subject matter of the summer research project is often related to a student’s professional work. Research projects typically involve studying a real world data analysis problem, in a wide range of data types (biomedical, clinical, financial, energy, psychological or social). Each project involves understanding the data structure, conducting an efficient data analysis, and writing a full report with the guidance of a faculty mentor. The research project report is expected to present thoroughly and in depth the data set studied, the methods computationally-implemented, and the results obtained. To pass Math 6315, a student writes a project report which must be approved by his/her supervisor and a summary of the project report must be provided to the Director of Graduate Studies.

Scholastic Requirements


Graduate students must maintain a minimum grade point average of 3.00 in all course work to be considered in good standing. Students not in good standing cannot receive a graduate degree and can be declared ineligible for support with a graduate assistantship (IA, TA or RA).