Computational Mathematics and Statistics

Prepare yourself for a high-demand career in the ever-growing fields of computational sciences, data science and data analytics. As a student in Duquesne’s M.S. in computational mathematics & statistics program, you will gain advanced skills and knowledge in areas such as theoretical foundations of mathematics and statistics along with computational methods and practical applications related to data science and other areas of mathematics and statistics.

Horizon-expanding electives will teach you about artificial intelligences, machine learning, statistical computing and much more. You will also develop advanced programming skills and gain experience working with large-scale data and high-performance computing systems.

You will learn how to use software such as R, Python, SAS and MATLAB to analyze data and draw conclusions, develop algorithms to solve mathematical problems, learn how to use numerical methods to solve problems and analyze algorithms for accuracy and efficiency.

You'll also learn how to apply statistical methods and machine learning algorithms to analyze and interpret data and explore parallel computing and distributed systems toward more efficient processing of large-scale data and complex mathematical problems.

 

Degree

Master's

School

School of Science and Engineering

Required Credit Hours

36

Program Features

The program offers the following features:

  • 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 our faculty's key strengths: a strong commitment to teaching and active research programs in computational fields. You will learn from the best as you prepare for your career goals.

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. 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.

Ideally, as you apply for admission to the master’s program, you 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, you 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.

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.

International Students

International students might need to submit English language test scores. Note that we offer a Pathway Program for students who need to improve their English language skills but want to take some computational mathematics and statistics coursework at the same time.

For all applicants, there is no fee for the initial online application. But you may need to pay a fee to a third party to submit supporting materials, such as international credit evaluations and satisfactory test scores on the TOEFL for non-English language speakers.

B.S./M.S. Accelerated Program

The Department of Mathematics & Computer Science offers a combined B.S./M.S. program to students who are high-achieving in their undergraduate studies. Once admitted to the program, you have the opportunity to apply graduate credits earned while an undergraduate toward fulfilling requirements of both your departmental B.S. and the M.S. You could potentially complete both the B.S. and M.S. degrees in as little as five years.

To earn both the B.S. and M.S., you must earn at least 150 credits, 30 of which must be graduate credits (500-level or above) fulfilling requirements of the master's in computer science program. No more than 15 of these 30 graduate credits can be taken while you are an undergraduate.

As an undergraduate student enrolled in the combined-degrees program, you also enjoy the following advantages:

  • 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 your senior year with graduate school applications and admission decisions.

Application Requirements

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 at least 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 & 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.


Program Requirements

The core of the program consists of 1.5-credit mini-courses, consisting of four courses in each of the following disciplines: mathematics, computer science and statistics (12 total courses). 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 our 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 our 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 be offered. 

Elective offerings in recent years have included:

  • CPMA 550 Computer Networks
  • CPMA 555 Web-based Systems
  • CPMA 560 Algorithms/Graph Theory
  • CPMA 563 Numerical Differential Equations
  • CPMA 566 Operations Research
  • CPMA 573 Statistical Computing
  • CPMA 574 Prediction and Classification Modeling
  • CPMA 575 Data Mining and Data Science Analytics
  • CPMA 580 Artificial Intelligence/Cognitive Science
  • CPMA 582 Machine Learning
  • CPMA 590 Advanced Operating Systems
  • CPMA 590 Data Compression
  • CPMA 591 Database Management Systems

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 requirement 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 & statistics faculty advisor, a first reader and the Graduate Studies Committee, a student may write a thesis/project, worth 6 credits toward the 36 required for a degree, to be begun after completion of 18 credit hours. Depending on your background and interests, this portion of the program provides you 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 & 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 might include:

  • Mathematics: Maple, MATLAB;
  • Computer Science: Python, C++, Linux, Windows
  • Statistics: SAS, R, JMP, SPSS.

 

FAQs

About the M.S. in Computational Mathematics & Statistics

9 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 6 graduate credits to be a full-time student.
The program requires 36 credits. It 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 3 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 & statistics program while taking only evening courses, and we expect to continue to offer enough evening classes to make this possible in the future.

Since 2019-20, all of the program's core courses have been 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. But 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. But students who have earned at least 18 credits in the program can request that they be allowed to earn 6 credits through successful completion of a project or a thesis.

You would complete a thesis or project under a faculty member's supervision by applying some of the knowledge and skills acquired in one or more of the program's three disciplines to a question or problem of interest. You would then write a paper describing your answer to the question or solution to the problem and presents your work at a public "defense." 
Yes, the computational mathematics & 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.

Financial Aid

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 & 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 & 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 & statistics students who have done well during their first year have been able to find reasonably well-paid internships during the following summer.

FAQs

About Funding Your Degree

Costs vary from year to year; see the graduate tuition rates page for details. For the 2022-23 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.