Mathematics

Hybrid courses

The following courses for the math M.A.T. are typically offered in a synchronous hybrid format and can be taken in-person or virtually at a distance. They are offered in a two-year cycle, usually in the afternoons after 3:30 p.m. Pacific time to accommodate in-service teachers.

• EDCI 4110: Geometric reasoning (spring of even-numbered years)
• EDCI 4130: Probability and data analysis (spring of odd-numbered years)
• EDCI 4160: Proportional and algebraic reasoning (fall of odd-numbered years)
• MTHE 4090: Algebraic and functional reasoning (fall of even-numbered years)
• MTHE 4100: Proof and viable argumentation (spring of even-numbered years)
• MATH 3910: Modern geometry (every spring)
• MATH 3880: History of mathematics (spring of odd-numbered years)

Online courses

Many 3000+ and 4000+ mathematics and statistics courses are offered asynchronously online as video courses through Engineering Outreach. For a complete listing, contact the department at mathstat@uidaho.edu.

Degree requirements

The Math M.A.T. degree requires 30 credits, up to 12 of which may be transferred.

• At least 20 credits must be in mathematics, statistics, and mathematics education. These courses may be at the 3000+ level
• At least six credits in professional courses in Education (5000 level)

Explore program courses in the University Catalog

Related clubs and organizations

• Graduate and Professional Student Association (GPSA)
• Math Club

As a Math M.A.T. student, you are not required to complete research as part of your degree, but you may choose to pursue research opportunities based on your interests and goals.

Beginning Fall 2026, M.S. students appointed as Teaching Assistants will receive an annual support package that includes:

• Base stipend: $22,089.60 for the 9-month academic year
• In-state tuition: fully covered by the program
• Out-of-state tuition: waived for non-resident students
• Health insurance: Student Health Insurance Program premiums not covered
• Summer support: additional scholarships up to $8,000, depending on funding availability

University of Idaho is committed to making graduate education accessible and helping students navigate the cost of earning an advanced degree. In addition to financial aid and scholarship opportunities, many graduate students receive funding through assistantships, research opportunities and other forms of academic support.

Here are a few key resources to help you understand graduate tuition, funding opportunities and available financial support:

• Submit your FAFSA: Completing the Free Application for Federal Student Aid (FAFSA) is an important first step in accessing federal financial aid and certain institutional funding opportunities.
• Estimate your cost of attendance: Visit U of I’s cost of attendance page to explore estimated tuition, fees and living expenses associated with your graduate program.
• View a breakdown of tuition and fees: Visit the Student Accounts page to explore current tuition rates, fees and detailed cost information based on your program, residency status and enrollment level.
• Explore scholarships and graduate funding opportunities: Graduate students may qualify for scholarships, fellowships and other funding opportunities based on academic achievement, area of study and professional experience.
• Learn about assistantships: Many graduate programs offer Research Assistantships (RAs), Teaching Assistantships (TAs) or Graduate Assistantships (GAs), which may provide tuition support, stipends and valuable professional experience. Assistantship availability and funding levels vary by program and department.
• Connect with your program: Some graduate funding opportunities are coordinated directly through academic departments or faculty research projects. Prospective students are encouraged to review department funding information and speak with program representatives about available opportunities.

If you have questions about financial aid, scholarships or graduate funding, U of I’s experienced financial aid counselors and graduate program staff can help you explore options and make informed financial decisions throughout the admissions process.

View financial aid resources

Have questions about the program, research opportunities or the graduate student experience? Connect with our program team for personalized guidance about curriculum, faculty mentorship, application requirements and graduate funding opportunities.

Mathematics and Statistical Science contact:
Lana Unger
mathstat@uidaho.edu

For questions related to admissions, application materials, transcripts or enrollment steps, contact Graduate Admissions:

Graduate Admissions contact:
graduateadmissions@uidaho.edu
208-885-4001

Interested in research areas or finding a faculty mentor? Explore faculty expertise, research interests and advising opportunities on the department’s faculty page.

Applicants for the Mathematics M.A.T. must meet the following admission requirements:

Program availability:

• Concentration: Non-thesis
• Semester intake: Fall, Spring
  • Not eligible for international applicants who require F-1
• Deadlines: General application deadlines
• Start dates:
  • View the academic calendar to see start and end dates

University requirements:

• Education level: Bachelor's degree in a similar field from an accredited or recognized institution (earned or expected before the start of the graduate program)
  • Transcripts for all post-secondary education will be required. Unofficial transcripts may be used for initial admission review. Official transcripts sent by the issuing institution(s) will be required if admitted. View more information on the Graduate Admissions page.
• GPA: 3.0 (Applicants with a lower undergraduate GPA who have relevant professional experience in the field, have already earned a graduate degree, or have completed graduate-level credits may still be considered for admission with approval from the academic program.)
• GRE: Not required
• Letters of recommendation: Three
• Resume
• Statement of Purpose
• Valid picture ID (required to verify students’ identity and will be kept confidential)
• English proficiency (for applicants whose education was completed in countries where English is not an official language).
  • Accepted tests: TOEFL: 4.5, IELTS: 6.5, Duolingo: 115, PTE-A: 58. Learn what qualifies as proof of English proficiency.
• Application Fee: $50

Application and admission process:

Applications are submitted online and are specific to the program and term selected. Applicants seeking admission to multiple programs must submit a separate application for each program.

Before submitting an application, applicants must provide personal and academic information from all post-secondary institutions attended, recommender information, required program-specific materials, and their intended program and start term.

Applications are reviewed for admission by the academic program. Only complete applications, including required letters of recommendation and payment of the application fee, will be forwarded for evaluation and admission decision. Applicants are strongly encouraged to complete their applications early to allow sufficient time for a thorough review.

Visit Graduate Admissions to learn more and start your application.

Timothy R. Johnson, Department Chair and Professor

• Bayesian statistics
• Choice and ranking data
• Missing data
• Simulation-based inferential methods
• Statistical disclosure control

Hirotachi Abo, Professor

• Algebraic geometry
• Commutative algebra
• Multi-linear algebra
• Multi-linear algebra from an algebra-geometric viewpoint

Lyudmyla Barannyk, Associate Professor

• Numerical analysis
• Partial differential equations

Erkan Buzbas, Associate Professor

• Metascience
• Replicability
• Reproducibility
• Bayesian statistics
• Computational methods

Sarah Castle, Assistant Professor

• Mathematics education
• Computing education

Yanghyeon Cho, Assistant Professor

• Survey sampling
• Small area estimation
• Statistical genetics
• Causal inference
• Imputation

Somantika Datta, Professor

• Applied harmonic analysis
• Frame theory
• Signal processing

Rob Ely, Professor

• Mathematical learning and reasoning in calculus and algebra
• Math history
• Mathematical play

Frank Gao, Professor

• Functional analysis
• Probability theory
• Approximation theory
• Deep learning

Esteban Hernandez-Vargas, Associate Professor

• Mathematical immunology
• Control theory
• Machine learning
• Applied mathematics

Jennifer Johnson-Leung, Professor

• Number theory
• Automorphic forms and representations
• Foundations of cybersecurity
• Geometry of information

Mark J. Nielsen, Professor

• Discrete and combinatorial geometry

Chris Remien, Associate Professor

• Mathematical biology
• Bioinformatics

Benjamin Ridenhour, Associate Professor

• Biomathematics
• Biostatistics

Stefan Tohaneanu, Professor

• Commutative algebra
• Discrete geometry
• Algebraic coding theory

Hong Wang, Professor

• Graph theory
• Combinatorics

Alexander Woo, Professor

• Combinatorial algebraic geometry
• Combinatorics of Coxeter groups

Tiantian Yang, Assistant Professor

• Generalized distributions
• Mathematical statistics

Fan Yi, Assistant Professor

• Image monitoring
• Statistical process control (SPC)