Skip to main content
University of North Dakota
University of North Dakota
    • Admitted Students
    • Current Students
    • Families of Current Students
    • Faculty & Staff
    • Alumni
    • Email
    • Blackboard
    • Campus Connection
    • Employee Self-Service (HRMS)
    • Starfish
    • Degree Map
  • Directory
  • Academics
  • Admissions
  • Student Life
  • Research
  • Athletics
  • Majors & Programs
  • About
University of North Dakota
  • Academics
  • Admissions
  • Student Life
  • Research
  • Athletics
  • Majors & Programs
  • About
  • Request Info
  • Visit
  • Apply
  • Request Info
  • Visit
  • Apply
Applied Statistics Student Working on Laptop
  • Home
  • Program Finder
  • Applied Statistics
print Print Page

Master's in Applied Statistics

Master of Science (M.S.)

Immerse yourself in the study of applied statistics and build your skills as an analytical thinker and problem solver.

Bring data to life with UND's Master of Science in Applied Statistics. Set yourself apart with an education in a variety of foundational courses and statistical software packages.

Program type:
Master's Degree
Format:
On Campus or Online
Est. time to complete:
2 - 3 years
Credit hours:
33
  • Requirements
  • Tuition & Aid
  • Why UND Online?
  • How to Apply

Request Information

Why earn a master's in applied statistics?

Application Deadline
Fall:
Aug. 1

Our department features small classes and collaborative relationships with industry partners. Working with the same data software programs that employers are looking for, you’ll build crucial skills in data visualization, predictive modeling and data analysis techniques.

Through the master's in Applied Statistics at UND, you’ll gain:

  • Competency in high level statistics including:
    • Problem solving
    • Data analysis
    • Data science and data mining
    • Machine learning
    • Big data
  • The range of skills required to carry out programs of independent research as a data scientist
  • The ability to effectively use a variety statistical software packages such as Python, SAS and R
  • Analytical skills needed to work as a professional data applied statistics scientist

Applied Statistics Master's at UND

  • Take courses in multivariate statistics and time series.

  • Learn to harness the power or Python, SAS and R software.

  • Be part of a Big Data Hub. Data science is an ongoing area of research funding for UND.

  • Gain a competitive edge in the workforce through our Accelerate to Industry (A2i)™ program. This workforce readiness program provides immersive job training experiences for graduate students and postdoctoral researchers.

  • Study at a Carnegie Doctoral Research Institution ranked #151 by the NSF. Students are an integral part of UND research.

  • Enhance your professional skills at 60+ free workshops offered through the UND School of Graduate Studies. Our goal is to provide you with the workforce skills and job search strategies to succeed.

What can I do with a master's in applied statistics?

93K

Median annual salary for mathematicians and statisticians

U.S. Bureau of Labor Statistics

33%

Anticipated job growth for mathematicians and statisticians

U.S. Bureau of Labor Statistics

Graduates of UND's graduate applied statistics program play critical roles in many industries, including business, engineering and more. Experts are in demand in a range of jobs including:

  • Actuary
  • Business analyst
  • Data engineer
  • Data mining analyst
  • Data scientist
  • Data visualization
  • Financial quantitative analyst
  • Statistical software designer
  • Statistician

 

Applied Statistics Master's Courses

MATH 421. Statistical Theory I. 3 Credits.

Discrete and continuous random variables, expectation, moments, moment generating functions, properties of special distributions, introduction to hypothesis testing, sampling distributions, Central Limit Theorem, curve of regression, correlation, empirical regression by least squares, maximum likelihood estimation, Neyman-Pearson lemma, likelihood ratio test, power function, chi-square tests, change of variable, "t" and "F" tests, one and two-way ANOVA, nonparametric methods. Prerequisite: MATH 265. F.

STAT 500. Computing for Statistics. 1 Credit.

Use and programming of computer packages for statistics. Preparation for use of software in graduate-level statistics courses. Packages covered may include R, Python, SAS, and others. Prerequisites: At least one course in statistics, and prior programming coursework or experience. Prerequisite: At least one course in statistics and computer programming coursework or experience. F,SS.

STAT 541. Linear Statistical Models. 3 Credits.

Distributions of quadratic forms, general linear hypotheses of full rank, least squares, Gauss-Markoff theorem, estimability, parametric transformations, Cochran's theorem, projection operators and conditional inverses in generalized least squares, applications to ANOVA and experimental design models. Prerequisite: MATH 422 or consent of instructor. F.

STAT 543. Design of Experiments. 3 Credits.

Design and analysis of experimental data. Includes the use of factorial designs, Latin square designs, randomized block designs, split-plot designs and others. Prerequisite: STAT 541. S, odd years.

STAT 545. Multivariate Statistics. 3 Credits.

Theory-based statistical methods for analyzing and displaying multivariate data with applications in machine learning and data mining. Topics include inference in multivariate populations, multivariate analysis of variance, summarizing high dimensional data using principal component analysis, factor analysis, canonical correlation analysis, linear and quadratic methods of classification, cluster analysis, classification trees and random forests, multi-dimensional scaling, and support vector machines. Prerequisites: STAT 500, STAT 541, and MATH 442 or experience with linear algebra concepts. S, even years.

STAT 551. Statistical Graphics. 3 Credits.

Statistical graphics and visualization of one-, two-, or higher-dimensional data. Well-designed graphs and charts are essential for exploration of data, assessment of models, and presentation of results. Includes specific methods as well as general principles, such as effective use of color and motion. Prerequisite: STAT 500. F, even years.

Leaders that Do

Students at UND take chances, seek challenges and become leaders in the community.

Request Information

Explore More Options

Check out the faculty you'll work with at UND or discover additional education opportunities.

  • Department of Mathematics
  • Explore Similar Degrees
  • Meet the Faculty
Department Contact
Dr. Gerri Dunnigan
Department of Mathematics Chair
Grand Forks, ND 58202-0000
P 701.777.2882
gerri.dunnigan@UND.edu
    We use cookies on this site to enhance your user experience.

    By clicking any link on this page you are giving your consent for us to set cookies, Privacy Information.

    Ready to Enroll?

    • Request Information
    • Schedule a Visit
    • Apply Now
    • UND.info@UND.edu
    • 701.777.3000
    • YouTube
    • Instagram
    • Facebook
    • TikTok
    • Twitter
    • LinkedIn
    • Contact UND
    • Campus Map
    • Events Calendar
    • Explore Programs
    • Employment
    • Make a Gift
    University of North Dakota

    © 2022 University of North Dakota - Grand Forks, ND - Member of ND University System

    • Accessibility & Website Feedback
    • Terms of Use & Privacy
    • Notice of Nondiscrimination
    • Student Disclosure Information
    • Title IX
    ©
    UND.info@UND.edu
    701.777.3000 | 1.800.CALL.UND
    UND.edu/programs