School of Information Technology & Engineering
- Applied and Engineering Statistics
- Undergraduate Programs
- Graduate Programs
Applied and Engineering Statistics
Faculty
Professors: Carr, Gantz, Gentle, Greenberg, D.
Miller, Wegman (chair)
Associate professors: Bolstein, Habib, J. Miller, C. Sutton
Assistant professor: Bell
Adjunct professors: Andersen, Davis, Faxon,
Martinez, Sims, Sirgany, Solka
Course Work
The Applied and Engineering Statistics Department
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,
the social sciences, business, nursing, education, and
engineering. The department 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, 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 and in the College of
Nursing and Health Science, as well as in the School of
Information Technology & Engineering. 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 yet offer an
undergraduate degree in statistics, a variety of advanced courses
are available for inclusion in other degree programs.
Undergraduate Programs
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The Department of Applied and Engineering Statistics
offers a certificate program to complement undergraduate
degree programs in computer science, systems engineering,
electrical engineering, urban systems engineering, or
mathematics. Undergraduates majoring in other discipline areas
may be admitted to the certificate program at the discretion
of the department.
Because the demand for people with interdisciplinary
training, which includes a background in statistics and data
analysis, is great in the Washington metropolitan area,
this program expands the career options available to
students. Inquiries should be directed to the Department of
Applied and Engineering Statistics. Students who plan to work
toward the certificate should seek advice from the department.
Certificate Requirements
This certificate program requires 24 credits, consisting
of STAT 344, 362, and 354 or 554, along with five
courses chosen from STAT 455, 457, 463, 474, 498, 499, 544,
574 and OR 435, 442, 481.
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The undergraduate minor in data analysis is designed to
provide students with a background in data analysis and
statistical methodology. The minor is intended to
complement undergraduate degree programs in the School of
Information Technology and Engineering, College of Nursing
and Health Science, and the College of Arts and Sciences.
The minor requires 15 credit hours (five courses). The
foundation of the minor is a two-course sequence, either STAT
250/350 or STAT 344/354, a course in statistical
computing (STAT 362), and a course in data analysis (STAT
463). To complete the minor, an elective is chosen from a list
of approved courses or with concurrence of the
undergraduate program coordinator.
Program Requirements
This minor requires 15 credits, consisting of STAT
250/350 or STAT 344/354, STAT 362, STAT 463 and an elective
chosen from STAT 455, 477, 544, 554, CS 450, 480, SYST
473, or USE 410.
Graduate Programs
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Statistical science is regarded as one of the oldest and
most successful information technology subjects, focusing 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 M.S. program can be thought of in matrix form,
one dimension offering a choice of research or
professional options and the other dimension offering a choice of
subject emphases, including federal statistics, computational
statistics, statistical signal processing, applied statistics, and
engineering statistics. The research option is intended for
students planning to continue for the Ph.D. degree or to begin or
continue careers in statistical methodology research. The
professional option provides M.S. 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 to this program must
do the following:
- Hold a bachelor's degree from an accredited
institution with an appropriate undergraduate major.
Examples include mathematics, computer science, statistics,
and electrical engineering. Applicants must have
advanced preparation in mathematics, including calculus or
real analysis, basic statistics and probability, and matrix
theory or linear algebra.
Course work taken to correct deficiencies in
undergraduate preparation is not counted toward the degree.
- Demonstrate basic computer literacy.
The GRE is not required. It is recommended
particularly for those students wishing to compete for graduate
teaching assistantships, fellowships, or research assistantships.
Degree Requirements
Students in both the research and professional options
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. Applied Probability (STAT 544)
covers the major mathematical framework for statistical
theory and practice. Statistical Inference (STAT 652) provides
basic statistical theory. After completing this course, students
have the theoretical basis from which statistical methods
are derived.
Applied Statistics (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 Regression Analysis
(STAT 656), which focuses on determining the relationship
between two or more quantities possibly measured with error,
particularly with emphasis on broad scientific and
technological applications. From these basic elements, the
perspective M.S. student may choose one of five defined emphases
or may, with the concurrence of his or her advisor, design
a customized curriculum. The defined emphases are (1) applied statistics, (2) federal statistics, (3) computational statistics, (4) statistical signal processing, and (5) engineering statistics. Other courses may be chosen from any graduate STAT courses, except STAT 510, 512 and 530.
STAT 679 and STAT 798 may be repeated for credit with
departmental approval. Also, many courses from other
departments may be chosen with departmental approval.
Professional Option
The professional option focuses on the completion of
course work in modern statistical theory and practice. The
basic course work requirements include 30 credits. Twelve
credits must be the core courses taken by all M.S. students, with
18 additional credits taken from the approved list or with
the approval of the student's advisor. Students in this
program are encouraged to pursue a broad background in
statistical science and may elect to concentrate on applications of
statistical methodology to other disciplinary areas. A
student would normally complete the degree by taking 10
three-credit courses with no written reports such as a thesis and no
oral examination. A student would have to satisfy the
general degree requirements for graduate study.
A student in the professional option may write a
master's essay that 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 may be required to revise their essays
to develop their skills in preparing reports on technical
subjects. The essay is normally written in the context of
STAT 798 Master's Essay.
Students who complete the essay will take 27 credit
of inclass work and three credit of STAT 798 Master's
Essay. Students opting not to write an essay must take 30 credits
of in-class work.
Research Option
The research option requires 30 credits, of which 6
credits must be in independent research (thesis). Research is
done under the guidance of a faculty member. Research may
be carried out at the university or, if appropriate, at nearby
facilities. For example, students may pursue research at
their places of employment on topics of interest to their
employers, 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 degree
requirements for graduate study, candidates for 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 examination that concentrates
on, but is not limited to, the area on which the
thesis or report is written. The examination 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.
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The combined B.S./M.S. degree option provides a way
for George Mason students to earn an M.S. in Statistical
Science in a shorter period of time than if they had
graduated from a suitable George Mason B.S. program and then
applied to the M.S. program.
Admission Requirements
To enroll, the student must begin his or her M.S. work
within six months following completion of a B.S. degree in
any one of the IT&E major areas, or a B.S. in Mathematics
from the College of Arts and Sciences. Admission is
guaranteed to any student with an overall GPA of 3.000 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 combined B.S./M.S. program consists of a minimum
of 144 credits that satisfy the requirements for both the
B.S. and the M.S. in Statistical Science, with 6 credits of
overlap. Twenty-four credits are required for the M.S., provided
that the student has taken two of the following three courses
as part of his or her B.S. course work: STAT 544, 554, and 574.
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The graduate certificate in federal statistics is a
professional program 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 multidisciplinary 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 certificate program is extremely flexible and
can be tailored to the needs of students within the federal
statistical sector, but is also intended to be responsive to the
needs of those in state and local governments and those in the
private sector who support the statistical system.
Admission Requirements
Potential candidates should have a bachelor's degree,
including at least two courses in statistics and/or
mathematics. Applicants typically have degrees in diverse fields such
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 the certificate program courses
and elective courses. The certificate courses are aimed at
building the foundations of statistical analysis and survey
methods and consist of the following:
STAT 554 Applied Statistics
STAT 574 Survey Sampling I
STAT 634 Case Studies in Data Analysis
STAT 663 Statistical Graphics and Data Exploration
STAT 673 Statistical Methods for Longitudinal
Data Analysis
STAT 674 Survey Sampling II
STAT 679 Topics in Survey Design and Analysis
All these courses may be used for credit toward the M.S.
in Statistical Science. Students with a minimal background
in mathematics or statistics should consider taking STAT
530. STAT 530 is intended to enhance a student's
background and does not count toward the certificate.
For the certificate program, the student may choose any
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, marketing,
operations research, psychology, public administration,
sociology, and statistics. Some courses may have prerequisites for
which the student must qualify or seek a waiver from the
appropriate instructor.
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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 in the area of signal
processing. Course work for the graduate certificate can be
used for credit towards the M.S. in Statistical Science as well
as the M.S. 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 the School of
Information Technology and Engineering.
Admission Requirements
The certificate program in signal processing is open to
all students who hold a bachelor's degree in any scientific
or engineering discipline from an accredited university.
Interested persons not already in a George Mason degree
program should apply for admission in nondegree status.
Certificate Requirements
The certificate consists of five graduate courses (15
credits) in the area of signal processing. A cumulative GPA
of 3.000 is required, and at most one course with a grade of
C may be applied toward the certificate. The certificate
courses comprise two required foundation courses taken by all
students and three elective courses.
Foundation Courses
STAT 544 Applied Probability or ECE 528 Random Processes in Electrical or Computer Engineering
ECE 535 Digital Signal Processing
Elective Courses
ECE 638 Fast Algorithms and Architectures for Digital Signal Processing
ECE 665 Optical Signal Processing
ECE 728 Random Processes in Electrical Engineering, II
ECE 734 Detection and Estimation Theory
ECE 735 Data Compression with Applications to Speech and Image Processing
ECE 738 Advanced Digital Signal Processing
STAT 652 Statistical Inference
STAT 658 Time Series Analysis and Forecasting
STAT 662 Multivariate Statistical Methods
INFT 746 Stochastic Calculus
INFT 776 Real Analysis and Statistics
Ph.D. Study in Statistics
Doctoral study in statistics is available through two of
the university's Ph.D. programs. The Ph.D. in Information
Technology has an emphasis in statistical science with an
engineering focus. The Ph.D. in Computational Sciences
and Informatics has an emphasis in computational statistics
with a basic science focus. Both degrees are interdisciplinary
and allow the student a broad range of course and
research options. These programs are described elsewhere in this
catalog. Advanced courses in statistics at the Ph.D. level are
also listed under the respective Ph.D. program descriptions.
Students may obtain more information by contacting
the graduate coordinator in Science and Technology
II, Room 158, (703) 993-3645.
George Mason University:1999-2000 University Catalog: Catalog Index: School of Information Technology & Engineering:Applied and Engineering Statistics |
