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The Department of Mathematics and Statistics offers the Master of Science degree in applied statistics. The graduate program is designed primarily to prepare graduates for careers in business, industry, or government, but can be tailored to provide a solid foundation for doctoral studies in statistics. The graduate program in applied statistics is open to persons with bachelor’s degrees in a variety of fields besides mathematics and statistics. The prior mathematical training needed for entrance into the program has been kept to a minimum to accommodate students with undergraduate majors in fields such as biology, business, or one of the social sciences. The department makes provision for part-time degree candidates by offering all required courses in the late afternoon or evening.

Early consultation with the statistics graduate advisor is recommended, since the advisor works closely with the student in every phase of the program.


Applicants for admission are expected to meet the general requirements for admission to graduate study as established by the Graduate School. Applicants should have completed a calculus sequence that includes multivariable calculus and a course in linear or matrix algebra. Some experience in computer programming and enough background in probability and statistics to begin basic graduate courses in statistics is also required. This normally means one or two prior courses in probability and statistics, depending on content and level. Applicants with insufficient preparation may be admitted on the condition that they complete certain prerequisite work to be specified by the department at the time of admission. Because of course sequencing, it is best to enter the program at the beginning of fall quarter.

Degree Requirements

The Master of Science degree in applied statistics may be earned by satisfying the degree requirements described below. The applied statistics program allows students considerable latitude in designing a course of study. This program is primarily intended to prepare students for professional employment in business, industry, or government; however, it can also form a solid foundation for doctoral study.

All master’s degree candidates are required to pass a comprehensive written examination which must be taken at least one quarter before the expected date of graduation. The examination is ordinarily offered during fall quarter.

In addition to the requirements of the Graduate School, the following departmental requirements must be met to earn a degree in applied statistics. Full-time students normally take two years to complete this program.


Harry J. Khamis (graduate advisor), categorical data analysis, survival analysis
Makarand V. Ratnaparkhi, mathematical statistics, biostatistics
Munsup Seoh (program director), nonparametric statistics and computational statistics
Thaddeus Tarpey, multivariate statistics, mathematical statistics
Daniel T. Voss (CoSM Assoc. Dean), design and analysis of experiments
Weizhen Wang, testing hypotheses, biostatistics

Associate Professors
Kimberly Kinateder, stochastic processes and exit times
Shuxia Sun, resampling methods, time series

Financial Assistance

The department awards a limited number of graduate teaching assistantships annually to qualified applicants. Assistantships may be renewed for a second year; assistants can complete the requirements for a degree in two years. An assistant’s duties include classroom teaching, which is a meaningful aspect of the education of graduate students in the mathematical sciences. Other assistantships are sometimes available through research grants and contracts.

Course of Study

Required Courses 27

STT 661, 662 Theory of Statistics I and II*
STT 666, 667 Statistical Methods I and II*
STT 669 Introduction to Experimental Design*
STT 761 Theory of Linear Models
STT 791 Statistical Consulting
Elective Courses† 18

STT 601 Nonparametric Methods
STT 611 Applied Time Series
STT 624 Statistical Control Methods
STT 626 Survival Analysis
STT 664 Computational Statistics
MTH 606 Mathematical Modelling
MTH 607 Optimization Techniques
MTH 631-633 Real Variables I-III
CS 670 Systems Simulation
STT 702 Applied Stochastic Processes

STT 714 Statistical Modeling for Environmental Data

STT 721 Sampling Design
STT 740 Categorical Data Analysis
STT 744 Applied Multivariate Analysis
STT 762 Topics in Linear Models
STT 764 Topics in Experimental Design
STT 767 Applied Regression Analysis
Total 45

Note: With the prior approval of the statistics advisor, other appropriate courses, including courses from outside the department, may be used as electives. Credit will be allowed for STT 686 or STT 786, Independent Reading in Statistics and Probability, and STT 696 or STT 796, Topics in Probability and Statistics, only if approved in advance.

*Students who have taken STT 661, 662, 666, 667, or 669 or equivalent prior to entering the program will be required to take additional elective hours in lieu of the courses taken.

†From the 18 hours of elective courses, at least 12 hours must be chosen from among the 700-level electives.

Graduate School
E344 Student Union
Voice: (937) 775-2976
Fax: (937) 775-2453
E-mail: wsugrad@wright.edu
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