Introduction

The Mathematical Statistics Option (MSO) is an option within our program of master of sciences in applied mathematics. A student who fulfils the requirements of the MSO will receive, in addition to the master degree, a certificate of proficiency in statistics signed by the Dean of the College.

The program prepares students for work in fields which require statistical analysis- such as industry, medical fields or engineering. Core-courses requirements include graduate level probability, graduate level statistics, stochastic processes, time-series analysis, multivariate statistics, linear models and regression analysis.

Depending on interest, electives can be selected from courses in numerical methods, optimization, stochastic PDE, computational statistics, and courses offered by the Departments of Finance, Economics, Biology and Biochemistry, Physics and Computer Science.

The course is intended for students with a variety of backgrounds, mainly UH math undergraduates or incoming graduate students but also students from other departments or who have been out of a university environment for a while but who have the necessary mathematical background. Students from other disciplines, engineering, physics and so on will be required to take the course Basic Skills for the Applied Mathematician.

Full-time students are expected to complete the program in two years at a rate of three courses per semester. Part-time students are also welcome.

Degree Requirements

The Mathematical Statistics Option (MSO) beganin 2005 Fall Semester. A student who fulfils the requirements of the MSO will receive, in addition to the master degree, a certificate of proficiency in statistics signed by the Dean of the College.

To be admitted to the program, a student must have completed a bachelor's degree with a 3.0 GPA over the last 60 hours of all course work and should have a good background in mathematics. A student need not have majored in mathematics to be admitted. It is expected, however, that the student has completed at least 9 hours of mathematics at the junior or senior level, preferably in courses such as probability, advanced linear algebra and advanced calculus. When these requirements are not met a student may be provisionally admitted until successful completion of MATH 6377 (Basic Tools for Applied Mathematician). The 3 hours will not be counted as a part of the 30-hour requirement. Applicants with graduate degrees in science, mathematics, economics, or engineering may only be admitted by recommendation of the Committee on MSO, and with the approval of the Director of Graduate Programs in the Department.

All relevant regulations set forth in the Graduate Studies Bulletin and the Bulletin of the College of Natural Sciences and Mathematics must be observed. The requirements for the M.S. degree in Applied Mathematics, Mathematical Statistics Option, are as follows.

• Completion of a minimum of 30 credit hours (with a 3.0 GPA overall and no more than 3 grades at or below C+).
• Completion of the following courses with a grade of C or higher:
  • MATH 6382, 6383: Probability and Mathematical Statistics I, II
  • MATH 63XX: Linear Models and Regression Analysis, Multivariate Statistical Analysis
• Completion of the following two courses
  • MATH 63XX: Statistical Computing I
  • MATH 63XX: Stochastic Processes
• Completion of two more courses from the following list:
  • MATH 73XX: Topics in Probability
  • MATH 73XX: Data Mining
  • MATH 63XX: Time Series Analysis
  • MATH 63XX: Special Topics in Mathematical Finance (The subject varies from semester to semester; possible topics: Value at Risk, Real-Option Valuations, Valuation of Energy Derivatives, and Energy Risk Management)
• MATH 73XX: Computational Statistics (Markov Chains Monte Carlo, and Bayesian Statistics)
• MATH 73XX: Numerical Methods in Finance
• MATH 73XX: Econometrics of Financial Markets
• Other MATH courses at 6000 level or higher with the approval of the MSO Program Director

Contact Information

Professor Matt Nicol is in charge of the Statistics Option. Please contact him for more information on this program. e-mail: nicol@math.uh.edu.