Master of Science in Mathematics Online

Expand your career opportunities when you develop your mathematics expertise with high-demand abilities such as teaching, leadership, research, operations and management.

Apply by: 10/5/26
Start class: 10/19/26 Apply Now Apply Now

Program Overview

What does the online M.S. in Mathematics program offer?

Boost your credentials with a convenient Master of Science in Mathematics from Northwest Missouri State University. Whether you are specializing your skillset as a math educator or advancing your career in a different field, our 100% online program enables you to achieve your next career milestone on your schedule.

Strengthen your understanding of higher mathematics with our rigorous, yet rewarding, program. Explore an overview of modern data analysis methods, including Statistical Machine Learning (SML), elementary statistical concepts and computer methods in statistics, classical number theory, engineering and statistical modeling problems, and abstract algebra.

According to Emsi Burning Glass, projected job growth for middle and high school math teachers is between 5% and 6% over the next ten years. Future proof your education career when you optimize your resumé with this versatile degree. Our M.S. in Mathematics online prepares you to lead as a math specialist in middle and high schools, teach dual credit classes, and instruct at community colleges.

In addition to education, this program equips you with essential tools for upper-level mathematics roles in computer systems design, scientific and technical consulting, corporate management, and depository credit intermediation. Earn your Master of Science in Mathematics online to meet the demand for trained mathematicians.

What skills do graduates of the online M.S. in Mathematics at Northwest develop?

  • Expand your knowledge in new areas of data analysis, machine learning and statistical science
  • Analyze the relationships between variables and build statistical models to predict outcomes and support better decision-making
  • Understand the strategies and methods of database data analysis to drive business decisions
  • Gain the required advanced math credit to become certified to teach dual credit high school courses, or to teach math in a community college
What skills do graduates of the online M.S. in Mathematics at Northwest develop?
  • Expand your knowledge in new areas of data analysis, machine learning and statistical science
  • Analyze the relationships between variables and build statistical models to predict outcomes and support better decision-making
  • Understand the strategies and methods of database data analysis to drive business decisions
  • Gain the required advanced math credit to become certified to teach dual credit high school courses, or to teach math in a community college

What careers are available with an online Master of Science in Mathematics from Northwest?

  • Secondary School Teacher
  • Middle School Teacher
  • Operations Research Analyst
  • Directors of Business Development
  • Data Scientist
  • Statistician
What careers are available with an online Master of Science in Mathematics from Northwest?
  • Secondary School Teacher
  • Middle School Teacher
  • Operations Research Analyst
  • Directors of Business Development
  • Data Scientist
  • Statistician

Also available

Northwest offers a variety of specialized online education program options. Check out our other online education programs.

Total Tuition $12,960*
Program Duration As few as 12 months
Credit Hours 30

Accreditation:

AAQEP logo

Northwest Missouri State University is accredited by the Association for Advancing Quality in Educator Preparation (AAQEP) and is recognized by the Missouri Department of Elementary & Secondary Education™ (DESE) and the Higher Learning Commission.

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Need More Information?

Call 844-890-9304

Call 844-890-9304

Tuition

How much does the online M.S. in Mathematics at Northwest cost?

Our Master of Science in Mathematics online program offers affordable, pay-by-the-course tuition, which is the same for in-state and out-of-state students. All fees are included.

View additional tuition information+

Program Per Credit Hour Per Course Per Program*
M.S. – Mathematics $432 $1,296 $12,960

Important Refund Information

2nd day of class Last date for 100% refund for dropped course
4th day of class Last date for 75% refund for dropped course
6th day of class Last date for 50% refund for dropped course
8th day of class Last date for 25% refund for dropped course

Tuition breakdown:

Total Tuition $12,960*
Per Credit Hour $432

Calendar

Don’t forget these dates and deadlines

Northwest online programs are delivered in an accelerated format ideal for working professionals, conveniently featuring multiple start dates each year.

View full calendar +

TermProgram Start DateApplication DeadlineDocument DeadlineRegistration DeadlinePayment DueLast Class Day
Fall 18/24/268/10/268/13/268/17/268/19/2610/9/26
Fall 210/19/2610/5/2610/8/2610/12/2610/14/2612/4/26
Spring 11/11/271/4/271/5/271/6/271/7/272/26/27
Spring 23/8/272/19/272/24/272/26/273/2/274/23/27

Now enrolling:

Next Apply Date: 10/5/26
Next Class Start Date: 10/19/26
Ready to take the next steps toward

earning your degree?

Apply Now

Admissions

Understand our time-saving admission process

At Northwest, we’ve streamlined the admission process to help you get started quickly and easily. Please read the requirements for the Master of Science in Mathematics online, including what additional materials you need and where you should send them.

View all admission requirements +

Option 1

1. An undergraduate degree in mathematics or an undergraduate degree in a related field which includes the calculus sequence, a linear algebra course, and a transition to proof course. If the applicant’s undergraduate degree is missing one or more of these courses, a path to admission can be followed by completing either MATH 17301, MATH 17302, or both, with at least a B grade.

2. GPA Requirements:

  • A minimum overall grade point average of 3.0 on the undergraduate transcript
  • OR if undergraduate overall GPA is 2.74-2.99 then writing competency needs to be demonstrated*
  • OR if undergraduate overall GPA is 2.50-2.73 then writing competency needs to be demonstrated* and admission would be considered conditional (see Conditional Admission to Graduate Study)

*To demonstrate writing competency an applicant can:

a. Pass a departmental writing assessment** or

b. Score 3.5 or higher on the GRE Analytic Writing and a composite score of 280 or higher on the verbal and quantitative sections of the GRE General Test

** The writing assessment is not designed to test proficiency in a specific subject. It is rather a test to evaluate applicant’s abilities to critique, organize, and write a concise argument. Any student who fails the writing assessment must repeat the assessment within two weeks.

Option 2

Undergraduate mathematics majors within 30 hours of completing their undergraduate degree in Mathematics, with a GPA of 2.8 overall and 3.2 in mathematics may apply for admission to the accelerated program. Students in this option can complete their undergraduate and graduate degrees in Mathematics in 5 years. Please review the policy section on Accelerated Programs for additional information.

If you are a non-Missouri student, you should determine whether this program fits the certification requirements for your state.

Official transcript(s) can be emailed to: [email protected]. To submit official documents by mail, send them to:

Graduate Office
Northwest Missouri State University
800 University Drive
Maryville, MO 64468-6001

Have a question? Call us at 844-890-9304.

Click here for State Authorization information.


Admission Requirements:

  • Bachelor’s degree from an institutionally accredited institution
  • GPA of at least 2.75 on a 4.0 scale
  • Official transcripts from all institutions attended

Courses

What courses are included in the online M.S. in Mathematics at Northwest?

For the MS Mathematics online, the curriculum is comprised of nine courses worth 30 credit hours: 21 credit hours of required courses, 6 credit hours in Math electives, and 3 credit hours of other electives. For applicants whose undergraduate degree did not include the calculus sequence, a linear algebra course, and a transition to proof course, a path to admission can be followed by completing either MATH 17301, MATH 17302, or both, with at least a B grade.

Expand All

If applicable, these must be completed prior to taking any other math courses in the program.

Duration: 7 Weeks weeks
Credit Hours: 3
This is a survey course that covers essential topics in undergraduate mathematics. Pre-reqs: Calculus I, or consent of the instructor.
Duration: 7 Weeks weeks
Credit Hours: 3
This is a survey course that covers essential topics in undergraduate mathematics. Pre-reqs: Calculus I, or consent of the instructor.
Duration: 7 Weeks weeks
Credit Hours: 3
This course introduces the fundamental concepts of complex analysis, including complex numbers, analytic functions, contour integrals, and conformal mappings. It emphasizes both theoretical foundations and applications. Prerequisite(s): Admission to M.S. Mathematics or M.S.Ed. Teaching: Mathematics program or consent of instructor.
Duration: 7 Weeks weeks
Credit Hours: 3
This course is an introduction to the theory and applications of algebraic structures including groups and rings. Topics will include symmetric groups, cyclic groups, quotient groups, isomorphism, homomorphism, polynomial rings, and Euclidean domains. Prerequisite(s): Admission to M.S. Mathematics or M.S.Ed. Teaching: Mathematics program or consent of instructor.
Duration: 7 Weeks weeks
Credit Hours: 3
This course is an introduction to theories and applications involving the set of integers. Topics will include divisibility, prime numbers, congruences, Diophantine equations, Chinese remainder theorem, quadratic residues and reciprocity, and cryptography. Prerequisite(s): Admission to M.S. Mathematics or M.S.Ed. Teaching: Mathematics program or consent of instructor.
Duration: 7 Weeks weeks
Credit Hours: 4
This course provides an applied overview of modern data analysis methods, including Statistical Machine Learning (SML). Applications of SML may include science, marketing, finance, and other business and industrial disciplines. Under the supervision of the instructor, students will accomplish both lab activities and application-specific projects using modern SML or similar methods. The labs provide practical applications to enhance understanding and appreciation of each method. This course satisfies the Graduate Catalog research requirement. Prerequisite(s): Admission to M.S. Mathematics or M.S.Ed. Teaching Mathematics program, or consent of instructor.
Duration: 7 Weeks weeks
Credit Hours: 4
This course presents in rigorous fashion the fundamental concepts and tools of analysis-covering functions, countable and uncountable sets, limits, continuity, derivatives and integrals, and sequences. Most of the difficult points glossed over in elementary courses, as well as many advanced topics designed to give a good background for modern analysis and topology, are treated in details. Prerequisite(s): Admission to the M.S. Mathematics or M.S.Ed. Teaching: Mathematics program or consent of instructor.
Duration: 7 Weeks weeks
Credit Hours: 4
This course is an in-depth study of the bridge between geometry and calculus. We will investigate various avenues of this connection and develop tools for geometric exploration, justification, and modeling. These topics receive limited attention in undergraduate mathematics but result in powerful techniques for analysis and problem solving. Prerequisite(s): Admission to M.S. Mathematics or M.S.Ed. Teaching: Mathematics program or consent of instructor.

Choose 6 hours from the following areas: Mathematics, Computer Science, Data Mining.

Duration: 7 Weeks weeks
Credit Hours: 3
This course provides foundational skills needed in subsequent courses and includes an introduction to descriptive and predictive analytics. It includes a review of basic statistics, and introduction to widely-used data analysis tools. The course focuses on key foundations of importing, querying, and processing data and characterizing and visualizing information.
Duration: 7 Weeks weeks
Credit Hours: 3
This course will introduce students to basic statistics from a data science perspective. Statistical methods are a key part of data science. The primary objectives of this course are to explain how to apply various statistical methods to data science, how to avoid their misuse and to give advice on what is important and what is not. Topics include exploratory data analysis, data and sampling distributions, statistical experiments and significance testing, regression and prediction, classification, statistical machine learning, and unsupervised learning. It starts with simple statistics and then moves on to statistical methods used in data science algorithms. The concepts learned in this course should help students learn the statistical techniques required to implement data evaluation in data science tasks such as data cleaning, mining, and analysis.
Duration: 7 Weeks weeks
Credit Hours: 3
This course covers the design and development of exploratory diagrams and graphics for various data sets. The course may include concepts such as chart and graph design, networks, topological graphs, display of multi-dimensional data, effective use of space and color, animations, interactive visualizations, mapping, cartography, web data acquisition, and advanced visualization tools. Prerequisite(s): Coursework equivalent to general statistics and programming.
Duration: 7 Weeks weeks
Credit Hours: 3
A study of frequency distributions, measures of central tendency, variation, correlation and regression, application and interpretation of estimation procedures using normal, t, chi-square distributions and hypothesis testing. Prerequisite(s): Admission to M.S. Mathematics or M.S.Ed. Teaching: Mathematics program or consent of instructor.
Duration: 7 Weeks weeks
Credit Hours: 1-3
A supervised graduate-level research project for graduate students in the school. Prerequisite(s): 10 credit hours of 600-level mathematics. Repeatable: May be taken for 1 to 3 credit hours, and is repeatable up to a maximum of 6 credit hours.
Duration: 7 Weeks weeks
Credit Hours: 3
A study of analysis of variance, co-variance and regression. Use of SAS statistical package and interpretation of results. Prerequisite(s): Admission to M.S. Mathematics or M.S.Ed. Teaching Mathematics program, or consent of instructor.
Duration: 7 Weeks weeks
Credit Hours: 3
This course is an introduction to topology. It will cover topics such as topological spaces, metric spaces, continuity and convergence, compactness, and connectedness. Prerequisite(s): Admission to M.S. Mathematics or M.S.Ed. Teaching: Mathematics program, or consent of instructor.

Choose 3 hours not already taken in this list. This list includes education courses.

Duration: 7 Weeks weeks
Credit Hours: 3
This course provides foundational skills needed in subsequent courses and includes an introduction to descriptive and predictive analytics. It includes a review of basic statistics, and introduction to widely-used data analysis tools. The course focuses on key foundations of importing, querying, and processing data and characterizing and visualizing information.
Duration: 7 Weeks weeks
Credit Hours: 3
This course will introduce students to basic statistics from a data science perspective. Statistical methods are a key part of data science. The primary objectives of this course are to explain how to apply various statistical methods to data science, how to avoid their misuse and to give advice on what is important and what is not. Topics include exploratory data analysis, data and sampling distributions, statistical experiments and significance testing, regression and prediction, classification, statistical machine learning, and unsupervised learning. It starts with simple statistics and then moves on to statistical methods used in data science algorithms. The concepts learned in this course should help students learn the statistical techniques required to implement data evaluation in data science tasks such as data cleaning, mining, and analysis.
Duration: 7 Weeks weeks
Credit Hours: 3
This course covers the design and development of exploratory diagrams and graphics for various data sets. The course may include concepts such as chart and graph design, networks, topological graphs, display of multi-dimensional data, effective use of space and color, animations, interactive visualizations, mapping, cartography, web data acquisition, and advanced visualization tools. Prerequisite(s): Coursework equivalent to general statistics and programming.
Duration: 7 Weeks weeks
Credit Hours: 3
This course provides opportunities for participants to develop knowledge and understanding of leadership principles and the process of curriculum development as it relates to the roles and responsibilities of mathematics education leaders.
Duration: 7 Weeks weeks
Credit Hours: 3
This course will prepare students to follow best practices in data literacy to: define a problem; locate literature that provides evidence of issues related to the problem; select key information about the problem that could be studied and where action could be taken; find, select and organize data about the key information; run qualitative or quantitative analyses; present findings to the professor; and reflect on how this experience and new skills could impact their professional lives. Data analyzed in this class must be anonymized. Results from this course are not generalizable and may not be published or disseminated for scholarly peer review. This classroom project activity is for ongoing quality improvement of teaching practices.
Duration: 7 Weeks weeks
Credit Hours: 3
Students who complete this course understand and demonstrate the capability to promote the success and well-being of each student by applying the knowledge, skills, and commitments necessary for equitable protocols for student support, equitable access in a least restrictive environment, responsive practices for culturally responsive teaching and leadership, and a supportive school culture that ensures each student and family is treated fairly.
Duration: 7 Weeks weeks
Credit Hours: 3
This course is designed to assist experienced teachers in the public schools to become more aware of issues in education which have an impact upon them. Issues will be analyzed in terms of the historical and philosophical bases that have created the climate leading to these problems. Issues will be addressed in terms that help teachers cope in the teaching situation.
Duration: 7 Weeks weeks
Credit Hours: 3
This course is designed through field experience to develop the coordination, articulation, and monitoring of a guaranteed and viable curriculum. Students will conduct an audit of curriculum to demonstrate an understanding of the importance of how the designed curriculum is actually being taught in a school with fidelity. **Cannot be taken at the same time as EDUC 61668.**
Duration: 7 Weeks weeks
Credit Hours: 3
A study of frequency distributions, measures of central tendency, variation, correlation and regression, application and interpretation of estimation procedures using normal, t, chi-square distributions and hypothesis testing. Prerequisite(s): Admission to M.S. Mathematics or M.S.Ed. Teaching: Mathematics program or consent of instructor.
Duration: 7 Weeks weeks
Credit Hours: 1-3
A supervised graduate-level research project for graduate students in the school. Prerequisite(s): 10 credit hours of 600-level mathematics. Repeatable: May be taken for 1 to 3 credit hours, and is repeatable up to a maximum of 6 credit hours.
Duration: 7 Weeks weeks
Credit Hours: 3
A study of analysis of variance, co-variance and regression. Use of SAS statistical package and interpretation of results. Prerequisite(s): Admission to M.S. Mathematics or M.S.Ed. Teaching Mathematics program, or consent of instructor.
Duration: 7 Weeks weeks
Credit Hours: 3
This course is an introduction to topology. It will cover topics such as topological spaces, metric spaces, continuity and convergence, compactness, and connectedness. Prerequisite(s): Admission to M.S. Mathematics or M.S.Ed. Teaching: Mathematics program, or consent of instructor.
Duration: 7 Weeks weeks
Credit Hours: 3
This course embraces mathematical concepts, pedagogical strategies, and instructional techniques specifically for secondary school educators. Participants will investigate the interconnected nature of mathematical ideas and their relevance to effective teaching practices by conducting a systematic analysis and review of topics from the mathematical curriculum. Prerequisite(s): Any combination of 3 courses from MATH 17602, MATH 17605, MATH 17618, MATH 17639, MATH 17643, and MATH 17652.

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100% of classes are taught by professionals, not graduate assistants

*Tuition and fees are based on current rates. Textbooks and laptops are not included with tuition.

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