Phone: 703-993-3645
Web: www.gmu.edu/departments/aes

Faculty

• Professors: Carr, Gantz, Gentle, Wegman
• Associate professors: Bell, Bolstein (chair), Habib, J. Miller, C. Sutton
• Assistant professors: Davis, Rytikova
• Adjunct professors: Kamocsai, Keller, Moumen, Sims, Sirgany, Solka

Course Work

The Applied and Engineering Statistics Department (AES) offers all courses designated STAT in the "Course Descriptions" chapter of this catalog.

Statistical methods and methods for data analysis are crucial for researching and exploring the natural sciences, social sciences, business, nursing, education, and engineering. AES offers a variety of introductory courses as well as more advanced course work in specialized statistical methodology and applications. The focus of the department's offerings is applied, with special emphasis on computing, graphics and visualization, federal and survey statistics, and engineering applications of statistics and data analysis.

Introductory courses are targeted for undergraduates in the College of Arts and Sciences (CAS) and the College of Nursing and Health Science (CNHS), as well as in the School of Information Technology and Engineering (IT&E). The STAT 250–350 sequence is targeted for general audiences, while the STAT 344–354 sequence is targeted for technical and scientific audiences. STAT 362 deals with computer statistical packages and is appropriate as a second or third course for students from a wide variety of backgrounds.

Although the department does not offer an undergraduate degree in statistics, it does offer a certificate program in applied statistics and a minor in data analysis. Also, a variety of advanced undergraduate courses are available for inclusion in other degree programs.

Undergraduate Programs

Certificate in Applied Statistics

This program complements undergraduate degree programs in computer science, systems engineering, electrical engineering, civil and infrastructure engineering, and mathematics. Undergraduates majoring in other discipline areas may be admitted to the certificate program at the discretion of the department.

The program expands career options available to students because the demand is great in the Washington, D.C., metro area for people with interdisciplinary training, which includes a background in statistics and data analysis. Inquiries should be directed to AES. Students who plan to work toward the certificate should seek advice from the department's undergraduate coordinator.

Certificate Requirements

This certificate program requires 24 credits: STAT 344 or 346, 362, 354 or 554, and 474 or 574; and four courses chosen from ECON 445; STAT 498 or 499; OR 435, 442, or 481; and SYST 473.

Minor in Data Analysis

The minor provides students with a background in data analysis and statistical methodology. It is intended to complement undergraduate degree programs in the IT&E and CAS, especially computer science, economics, geography, mathematics, public administration, sociology, and systems engineering.

Requirements

The minor requires 15 credits: a core sequence of 6 credits, plus 9 credits of electives. Grades of C or better are required in all courses. At least 9 of the 15 credits must be in STAT courses.

To satisfy the core requirement, the student must complete one of these sequences with grades of C or better: STAT 250–350 or STAT 344–354. STAT 554 may be substituted for STAT 354. Mathematics majors may substitute MATH 351–352 for STAT 344–354, provided the 9 elective credits are all STAT courses. The 9 elective credits must be chosen from a list of courses approved by the undergraduate program coordinator in the Department of Applied and Engineering Statistics. Courses currently approved for the minor are ECON 445; STAT 362, 463, and 474; CEIE 410; CS 450; GEOG 300 and 311; GOVT 400; OR 435; SOCI 405; and SYST 473.

BS/Accelerated MS in Statistical Science

This degree option provides a way for Mason students to earn an MS in statistical science in less time than if they had first graduated from a suitable Mason BS program and then applied to the MS program.

Admission Requirements

Students must begin MS work within six months following completion of a BS degree in any one of the IT&E major areas, or a BS in mathematics from CAS. Admission is guaranteed to any student with an overall GPA of 3.00 in courses taken after the first two undergraduate years (60 credits), and with grades of B or better in the two 500-level STAT courses selected from STAT 544, 554, and 574.

Degree Requirements

The program consists of a minimum of 144 credits that satisfy the requirements for both the BS in the undergraduate major and the MS in statistical science, with 6 credits of overlap. Twenty-four credits are required for the MS, provided that the student has taken two of the following three courses as part of his or her BS course work: STAT 544, 554, and 574.

Graduate Programs

Statistical Science, MS

Statistical science is regarded as one of the oldest and most successful information technology subjects. It focuses on the conversion of raw data into information. In this graduate program, students are trained in the theory and practice of statistical methodology, particularly as they impinge upon high-technology applications.

The MS program offers a choice of the following subject matter emphases: applied statistics, computational statistics, engineering statistics, federal statistics, and statistical signal processing. Students usually select one of these emphases, or design a customized curriculum in conjunction with a faculty advisor. Students also select either the research or professional option. The research option is for students planning to continue with a PhD degree, or to begin or continue careers in statistical methodology research. The professional option provides MS degree qualifications to those seeking an expanded knowledge base in modern statistical theory and practice, but not wishing to pursue a research career. Such students might plan to work in applied statistics, go on to professional schools, teach statistics at a secondary level, or pursue other careers in which advanced work in statistical methodology is necessary or advantageous but in which independent research is not involved.

Admission Requirements

In addition to satisfying the general admission requirements for graduate study, all applicants must demonstrate basic computer literacy. They also must hold a bachelor's degree from an accredited institution in a field that includes course work in calculus or real analysis, matrix or linear algebra, and calculus-based probability and statistics. Applicants with degrees in such fields as mathematics, computer science, statistics, and engineering automatically meet this requirement. For applicants with degrees in other fields, this requirement is normally satisfied if students have successfully completed courses equivalent to the following Mason courses: MATH 113, 114, 213, 203 or 322; and STAT 344 or MATH 351. Course work taken to correct deficiencies in undergraduate preparation is not counted toward the degree.

While the GRE is not required for admission, it is recommended for students competing for graduate teaching assistantships, fellowships, and research assistantships. International students from non-English-speaking countries who seek a graduate teaching assistantship should take the Test of Spoken English in addition to the TOEFL, which is required for admission.

Degree Requirements

In addition to meeting the general requirements that apply to master's degrees at Mason, all students must complete the 12-credit core requirements for the degree:

• STAT 544 Applied Probability
• STAT 554 Applied Statistics
• STAT 652 Statistical Inference
• STAT 656 Regression Analysis

The core course work covers the basic elements of statistics at the graduate level. STAT 544 covers the major mathematical framework for statistical theory and practice. STAT 652 provides basic statistical theory. After completing this course, students have the theoretical basis from which statistical methods are derived.

STAT 554 is a survey of statistical methods that have become the backbone of statistical practice. Focus in this course is on techniques that quantify random behavior. The final core course is STAT 656, which focuses on determining the relationship between two or more quantities possibly measured with error.

Students build on these core requirements by choosing one of five defined emphases, or by designing a customized curriculum with advisor concurrence. The defined emphases are applied statistics, computational statistics, engineering statistics, federal statistics, and statistical signal processing.

Each emphasis area requires students to select four courses from a specific list, and two approved electives. The lists are as follows:

• Applied statistics: STAT 574, 655, 660, 662, 665, 668
• Computational statistics: STAT 657, 663, 751; CS 652
• Engineering statistics: STAT 645, 655, 658, 758; OR 635
• Federal statistics: STAT 574, 634, 660, 663, 665, 673, 674
• Statistical signal processing: STAT 658, 662, 758; ECE 535

Elective courses may be chosen from any graduate STAT courses except STAT 510, 530, 535, 700, and 701. Only one of STAT 501–503 can be applied to the degree requirements. STAT 779 and 789 may be repeated for credit with approval of the graduate coordinator. Also, certain courses from other departments may be chosen with approval of the department chair, generally not to exceed 6 credits.

Students select either the professional or research option, depending on career ambitions. This choice should be made no later than the end of the semester in which 15 credits have been completed.

Professional Option

The professional option focuses on completing course work in modern statistical theory and practice. A total of 30 credits is required for the degree. Twelve credits must be in the core courses taken by all MS students, with 18 additional credits taken from the approved list or with advisor approval. Students electing this option are encouraged to pursue a broad background in statistical science, and they may wish to concentrate on applications of statistical methodology to other disciplines.

Students who select the professional option may elect to write a master's essay. This is not an original research report but a scholarly essay on a topic of current interest in the statistical science discipline. The essay is usually about 20 to 25 pages long and demonstrates the student's ability to read and synthesize the current technical literature into a scholarly essay. The essay is evaluated by the student's advisor, taking into account the comprehensiveness of the coverage of the scientific literature, the accuracy of presentation and interpretation, and the literary style. Students are notified of their evaluations, and they may be required to revise their essay to develop their skills in preparing reports on technical subjects. The essay is usually written in the context of STAT 798 Master's Essay. Students who complete the essay take 27 credits of course work and 3 credits of STAT 798 Master's Essay. Students opting not to write an essay must take 30 credits of course work.

Research Option

The research option requires 30 credits, including 6 credits that must be in independent research (thesis). Research is done under the guidance of a faculty member. Research may be carried out at Mason or, if appropriate, at nearby facilities. For example, students may pursue research at their place of employment on topics of interest to their employer, provided the research meets the standards of the university. The remaining 24 credits must include the 12 core credits, and elective courses taken from the approved list or added with the consent of the thesis advisor.

In addition to satisfying the general university requirements for a master's degree, candidates with the research option must do the following:

• Submit a thesis or report based on the research to the student's thesis committee, which must give preliminary approval. The composition and appointment of this committee follows graduate program policies.
• Pass a final oral exam that concentrates on, but is not limited to, the area on which the thesis or report is written. The exam is administered by the student's thesis committee, and all interested members of the graduate faculty are invited to attend and participate in the questioning. The thesis committee makes the final decision on whether the candidate passes or fails.

Certificate in Biostatistics

(Joint program with the CNHS)

The certificate prepares participants to apply statistical methods to quantitative analysis of health care issues. It is aimed at health scientists and professionals in government agencies such as the National Institutes of Health, pharmaceutical companies, research hospitals, public health agencies, and other medical research organizations that design medical experiments and analyze and interpret increasingly complex health-care data. The program will also help prepare students to begin careers in such organizations. The certificate is taught jointly by faculty from the statistics and health science programs.

Admission Requirements

Students must hold a bachelor's degree and have earned a GPA of 3.00 in the last 60 credits. The degree must be from a regionally accredited institution of higher education in a discipline related to health science or statistics. Such fields include, but are not limited to, medicine, biology, nursing, health science, biostatistics, statistics, mathematics, and psychology. A course in statistics and a course in calculus at the undergraduate or graduate level with grades of B or higher are also required. Applications are made either through IT&E or CNHS.

Program of Study

Students must complete one course from each of the five groups:

• STAT 535 or 554
• STAT 660 or 665
• HSCI 800 or STAT 656
• HSCI 801 or STAT 662
• HSCI 730

A minimum of 3 credits in HSCI courses and 6 credits in STAT courses must be taken at Mason.

Certificate in Federal Statistics

This professional program is targeted at upgrading the skills of practitioners. The federal statistical system is a complex data collection and analysis system that requires a wide variety of multi-disciplinary skills for its maintenance. The federal statistics certificate is intended to respond to the need for broad training in statistics; survey methods; data analysis, including graphics and data visualization; databases and data security; parallel computation and related technology; geographic information systems; and issues of statistics and public policy. The program is extremely flexible and can be tailored to the needs of students within the federal statistical sector, but it is also intended to be responsive to the needs of those in state and local governments, and those in the private sector involved in the collection, interpretation, or statistical analysis of federal data.

Admission Requirements

Potential candidates should hold a bachelor's degree, and should have taken at least two courses in calculus and one course in probability or statistics at the 300 level or higher. The recommended minimum preparation includes MATH 113–114 and STAT 344 or their equivalents. Students with a minimal background in mathematics or statistics should consider taking STAT 530 or SYST 500; it does not count toward the certificate. Candidates must also be computer literate. Applicants typically have degrees in such fields as sociology, economics, engineering, mathematics, statistics, and business. Candidates should inquire with the certificate coordinator for details of program planning. Courses are offered in late afternoon and evening and are particularly suitable for part-time students.

Certificate Requirements

The certificate program consists of 15 credits (five courses), which are selected from program courses and electives. The courses build the foundations of statistical analysis and survey methods. They consist of the following:

• STAT 510 Statistical Foundations for Technical Decision Making
• STAT 535 Analysis of Experimental Data
• STAT 554 Applied Statistics
• STAT 574 Survey Sampling I
• STAT 634 Case Studies in Data Analysis
• STAT 663 Statistical Graphics and Data Exploration
• STAT 665 Categorical Data Analysis
• STAT 673 Statistical Methods for Longitudinal Data Analysis
• STAT 674 Survey Sampling II
• STAT 779 Topics in Survey Design and Analysis

All of these courses, with the exception of STAT 510 and 535, may be used for credit toward the MS in statistical science. Credit is granted for only one of STAT 510, 535 and 554.

For the certificate program, students must choose three of the certificate courses plus two elective courses chosen with the consent of the certificate coordinator. The electives are intended to provide a broad background supportive of the multidisciplinary needs of complex statistical systems. They include courses from computer science, economics, geography, information systems, operations research, public administration, sociology, and statistics. Only one course (3 credits) can be outside the STAT program, and must be approved by the AES department chair. Suggested electives include STAT 544, 655, 656, 657, 660, 662, 664; CSI 703; ECON 637; OR 541, 542; PUAD 741, 742; and SOCI 631. Some courses may have prerequisites for which students must qualify or seek a waiver from the appropriate instructor. A cumulative GPA of 3.00 is required, and no more than one course with a grade of C may be applied toward the certificate. Only one of STAT 501–503 can be applied toward the 15 credits required for the certificate.

Certificate in Signal Processing

The Department of Applied and Engineering Statistics, in conjunction with the Department of Electrical and Computer Engineering, offers the certificate in signal processing, which provides graduate students with a program of courses and laboratory experience. Course work for the graduate certificate can be used for credit toward the MS in statistical science as well as the MS in electrical engineering. The primary purpose is to provide a well-defined target for students who want to advance or update their knowledge in this fast-moving field. The certificate may be pursued concurrently with any of the graduate degree programs in IT&E.

Admission Requirements

The program is open to all students who hold a bachelor's degree in any scientific or engineering discipline from an accredited university.

Certificate Requirements

The certificate consists of five graduate courses (15 credits) in signal processing. A cumulative GPA of 3.00 is required, and no more than one course with a grade of C may be applied toward the certificate. The certificate courses consist of two required foundation courses and three elective courses. See the list of courses under Certificate in Signal Processing in the Electrical and Computer Engineering section of this chapter.

PhD Study in Statistical Science

Doctoral study in statistics is available through two of Mason's PhD programs, both of which are interdisciplinary and allow a broad range of course and research options. Within the PhD in computational sciences and informatics, students can select a concentration in computational statistics. This program is described in the School of Computational Sciences chapter. Within the PhD in information technology, students may designate a concentration in statistical science in their doctoral degree title. In that case, the degree conferred upon a graduating student would be PhD in information technology with concentration in statistical science. This program is described below.

Requirements for PhD in Information Technology with Concentration in Statistical Science

Students must satisfy all the requirements for the PhD in information technology degree, as described later in this section. In addition, the following requirements must be met.

Admission Requirements

Students are usually required to have an MS degree in statistics, mathematics, operations research, biological or physical sciences, economics, electrical engineering, or some related engineering or information technology area. Students with an MS in statistics are expected to have completed course work equivalent to the MS core courses STAT 544, 554, 652 and 656 with a 3.50 GPA. Students with MS degrees in other fields typically have completed some of these courses but not all. They may be admitted pro-visionally on successful completion of the remaining courses.

Qualifying Exams

Students seeking the PhD in information technology must pass a set of four exams from three different degree programs. For the concentration in statistical science, two of these exams must be chosen from the following course list:

• STAT 544 Applied Probability
• STAT 554 Applied Statistics
• STAT 652 Statistical Inference

Advanced Emphasis Requirement

Students with a concentration in statistical science must complete the following four courses as part of their 24-credit doctoral plan of study:

• IT 876 Measure and Linear Spaces
• IT 971 Probability Theory
• IT 972 Mathematical Statistics I
• IT 973 Mathematical Statistics II

The remaining four courses (12 credits) must be independent of the qualifying exams taken by the student, and must be approved by the doctoral supervisory committee, AES chair, and associate dean of IT&E. The courses must be numbered 600 or above (655 or above for STAT courses, excluding STAT 700–701).

Doctoral Supervisory Committee

Upon admission to the doctoral program, students are assigned a temporary advisor. No later than the end of the second semester of study, students should select a dissertation director and a doctoral supervisory committee. The chair of the committee must be a tenured faculty member in AES. (The chair is usually, but not necessarily, the dissertation director, if a tenured member of AES.) The doctoral supervisory committee, which consists of four members, must include at least two graduate faculty members from AES and at least one from another department in IT&E. The composition of the doctoral supervisory committee must be approved by the AES chair and IT&E associate dean. Permission for the comprehensive exam and the dissertation defense are requested from the IT&E associate dean on the basis of a written request and plan that has been approved by the supervisory committee and the AES chair.

For more information, see the section of this chapter titled Information Technology, PhD. E-mail specific questions to statistics@gmu.edu, or contact the graduate coordinator directly in Room 158, Science and Technology II, 703-993-3645.