Earn your M.S. in Computational Mathematics and Statistics
Computational Mathematics and Statistics
Stay in the Know. Advance your Career.
Prepare for a high-demand career in computational sciences, data science and data
analytics, with a 36-credit Master of Computational Mathematics and Statistics degree
from Duquesne University. Computational Mathematics and Statistics is an advanced
skills, career-preparation program that is perfect for those wishing to enhance their
knowledge beyond the undergraduate level. We offer:
Full and part-time enrollment options.
Interdisciplinary curriculum taught by industry-tested faculty. resources well above
proficiency regarding languages programming, mathematical and statistical software,
and other computational tools.
A STEM Designated Degree Program.
This degree takes advantage of faculty strengths: a strong commitment to teaching
and active research programs in computational fields. Students learn from the best
prepare themselves for their bigger goals after graduation.
What background do I need?
Although Computational Mathematics and Statistics is an interdisciplinary program
encompassing applied mathematics, statistics, and computer science, you are not expected
to have a background in all three of these disciplines. However, we do expect that
students applying for the program will have already demonstrated proficiency in undergraduate
majors-level STEM (Science, Technology, Engineering, and Math) courses.
In particular, to be admitted to the program typically requires that you have completed
coursework that is at least the equivalent of a minor, preferably a major, in at least
one of the three Computational Mathematics and Statistics disciplines of mathematics,
statistics, or computer science.
Students must complete Duquesne's online application, including submission of an updated resume.
Students should submit official transcripts from previous educational institutions.
These educational institutions should send the transcripts directly to Duquesne University.
Students must submit three letters of recommendation, with aleast two of them being
from references who can comment meaningfully on your prior academic performance
A personal statement of at most 500 words that explains why you are applying to the
Computational Mathematics and Statistics program and provides any other information
you wish the admissions committee to have.
Students must submit their exam scores from the GRE (the Duquesne school code is 2196 and the department code is 0703). Although we look at applications holistically and have no fixed numeric requirements,
generally speaking, we expect an applicant's GRE quantitative scores to be in the
top quartile. Very low verbal GRE scores can also be a detriment to admission.
International students might need to submit English language test scores;
see theInternational Studentssection below for more information. Also note that we offer aPathway Programfor students who need to improve their English language skills but want to take some
Computational Mathematics and Statistics coursework at the same time.
Ideally, applicants for admission to the program in Computational Mathematics and
Statistics leading to a Master of Science degree will have completed a bachelor's
degree in mathematics, computer science or statistics with at least a 3.0 grade point
average. For unconditional admission, an applicant must have completed two semesters
of calculus, one semester of a programming language similar to Java, and one semester
of calculus-based probability and/or statistics. Applicants who do not meet all these
requirements but have a strong academic and/or work background in one of the three
disciplines will also be considered on a case-by-case basis.
For all applicants, there is no fee for the initial on-line application. However,
you may need to pay a fee to a third party in order to submit supporting materials
such as international credit evaluations and satisfactory test scores on the TOEFL
for non-English language speakers.
The core of the program consists of twelve 1.5 credit mini-courses, four courses in
each of the following disciplines: mathematics, computer science, and statistics.
This portion of the program is designed to ensure a common knowledge base in the three
disciplines. Most courses in the core curriculum have a computational component using
a software package or programming language related to that particular core topic.
The core courses are:
Mathematics (prerequisites: Calculus I and II)
CPMA 511 Logic and Proof
CPMA 512 Linear Algebra
CPMA 515 Advanced Discrete Math
CPMA 518 Vector Calculus
Statistics (prerequisites: a calculus-based Probability and Statistics course, such
as Duquesne's MATH 301, or equivalent knowledge)
CPMA 521 Probability/Markov Chains
CPMA 522 Statistical Inference
CPMA 525 Linear Models
CPMA 526 Experimental Design
Computer Science (prerequisities: a major's level introductory programming course,
such as Duquesne's COSC 160, or equivalent knowledge)
CPMA 530 Programming Language: Python
CPMA 532 Data Structures
CPMA 535 Intro to Computer Systems
CPMA 536 Software Engineering
Each semester, at least one elective is offered in each of mathematics, statistics,
and computer science. Student interest is considered in deciding what electives will
The Computational Mathematics and Statistics program stresses real-life problems and
real-life experiences. To that end, all students in the Computational Mathematics
and Statistics program must register for and complete CPMA 599 Internship. The internship
requiement can be fulfilled in one of two ways:
Prior or current employment experience related to topics covered in the Computational
Mathematics and Statistics program, or
A supervised internship related to topics covered in the Computational Mathematics
and Statistics program.
With the approval of a Computational Mathematics and Statistics faculty advisor, a
first reader, and the Graduate Studies Committee, a student may write a thesis/project--worth
six credits toward the 36 required for a degree--to be begun after completion of 18
credit hours. Depending on the student's background and interests, this portion of
the program provides an opportunity to design a project or conduct research with a
significant computational component. Written and oral presentations of the results
are required for both thesis and project.
Virtually every course in the M.S. in Computational Mathematics and Statistics includes
a computational component requiring the use of tools appropriate to the discipline.
Although tools change frequently in these rapidly developing areas, typical examples
Mathematics: Maple, MATLAB;
Computer Science: Python, C++, Linux, Windows
Statistics: SAS, R, JMP, SPSS.
B.S./M.S. Accelerated Program
The Mathematics and Computer Science Department offers a combined B.S./M.S. program
to students who are high-achieving in their undergraduate studies. Students admitted
to the program have the opportunity to apply graduate credits earned while undergraduates
toward fulfilling requirements of both their departmental B.S. degree and the Computational
Mathematics and Statistics M.S. degree. A student in the program could potentially
complete both the B.S. and M.S. degrees in as little as five years.
In order to earn both the B.S. and M.S. degrees, the student must earn at least 150
credits, 30 of which must be graduate (500-level or above) credits fulfilling requirements
of the Master's in Computer Science program. No more than 15 of these 30 graduate
credits can be taken while the student is an undergraduate.
An undergraduate student enrolled in the combined-degrees program also enjoys the
Automatic approval for enrolling in Computer Science graduate courses, as long as
the course prerequisites are met
Provisional graduate admission before completion of the undergraduate degree (this
becomes regular admission once the B.S. is earned, assuming that the entrance QPA
requirements listed below are maintained)
Freedom from concern during his or her senior year with graduate school applications
and admission decisions
About the M.S. in Computational Mathematics & Statistics
Nine graduate credits is considered a normal full-time course load in our program.
The University considers a student who is enrolled in a graduate program and taking
six graduate credits to be a full time student.
The program requires 36 credits. The program is designed so that a well-prepared full-time
student beginning in a fall semester can complete the program in two years, typically
including at least one summer of work to fulfill--or have waived--the internship requirement.
A part-time student will typically require longer. For instance, at a rate of three
credits per fall-spring semester, the program would require just under six years.
Note that the maximum amount of time allowed by the University to complete a Master's
program is six years.
It has been possible to complete the Computational Mathematics and Statistics program
while taking only evening courses, and we expect to continue to offer enough evening
classes to make this possible in the future. As of 2019-20, all of the program's core
courses are offered in the evening, and typically several electives each semester
are also evening courses.
All students are required to either have paid work experience in areas closely related
to the program or to complete an approved internship, paid or unpaid, for credit.
The University supports students seeking internships in a variety of ways, including
providing advice on resume development and communicating internship opportunities.
However, the program does not provide or arrange internships. This is each student's
responsibility. A high percentage of our students have located well-paid internships
after successfully completing our program's core coursework.
A thesis or project is not required for the program. However, students who have earned
at least 18 credits in the program can request that they be allowed to earn six credits
through successful completion of a project or a thesis. A student completes a thesis
or project under a faculty member's supervision by applying some of the knowledge
and skills students have acquired in one or more of the program's three disciplines
to a question or problem of interest to the student. The student then writes a paper
describing their answer to the question or solution to the problem and presents their
work at a public "defense."
Yes, the Computational Mathematics and Statistics M.S. program is a science, technology,
engineering, and mathematics (STEM) program. Therefore, international students with
an F-1 visa may apply for a 24-month extension of their post-completion Optional Practical
Training under the STEM OPT extension program.
Strong applicants may qualify for graduate assistantships.
Graduate assistantships provide full or partial tuition remission and a stipend.
Teaching assistants primarily tutor undergraduate students taking low-level courses
in the department.
One teaching assistant also provides technical support for departmental computer labs.
Second year students may ask to have full responsibility for a course in order to
gain college-level teaching experience.
Research assistantships may be available subject to grant funding.
Graduate assistantships are typically only offered in the fall semester. An application
for admission to the Computational Mathematics and Statistics M.S. program with consideration
for an assistantship should be submitted no later than March 1,
All students are required to have either relevant job experience or an internship
before completing their degrees. Although the Computational Mathematics and Statistics
program does not have pre-arranged internship agreements, Duquesne's location in the
heart of PIttsburgh, the demand for students with the skill sets we teach, and our
relationships with local employers greatly facilitate placements. Historically, full-time
Computational Mathematics and Statistics students who have done well during their
first year have been able to find reasonably well-paid internships during the following
Frequently Asked Questions
About funding your MS in Computational Mathematics & Statistics
Costs vary from year to year; see the graduate tuition rates page for details. For the 2022-2023 academic year, the price of this program is $1,421
per credit - but this number changes annually.
In addition to the 25% tuition award offered for new students. The department awards a limited number of teaching assistantships each
year, typically to students entering in the fall. In the past, these assistantships
have required approximately 15-20 hours of teaching-related work per week during the
academic year in exchange for 9 tuition credits each semester and a modest stipend
toward living expenses. There might also be research assistantships available, based
on faculty grant funding. The University maintains a page of information on graduate financing.
To be considered for financial assistance, indicate on the initial online application form that you want to be considered for assistantships or other financial assistance.