Master of Science in Applied Statistics

Complete in as few as 5 semesters

Nationally recognized for employability and value

100 percent online, no GRE/GMAT required

Master of Science in Applied Statistics

Become the Solution

Our online Master of Science in Applied Statistics prepares you to analyze and interpret data in a variety of professional settings and industries. The coursework delivers insight into a broad spectrum of statistical methods that can be used to make predictions, devise experiments, and draw accurate conclusions.

During the program, you’ll build the advanced foundation required to perform a detailed and impactful analysis of data in the workplace. As a core component of the program, you’ll work with industry-standard statistical and data analysis software and conduct a thorough analysis of real datasets to solve real-world problems.

Build the specialized skills to meet the growing demand for statistics and data professionals.

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Program Overview

  • 100 percent online; ideal for busy professionals
  • No GRE Required
  • Three start dates per year
  • Accelerated format – 7 week courses
  • 30 credits; 10 courses

Admission Requirements

  • Hold a bachelor’s degree from an accredited institution
  • Strong math background with college coursework in calculus, linear algebra, and statistics
  • Completed application, resume, personal statements, and letters of recommendation
  • GRE/GMAT not required, no application fee
  • For details, please request information

Areas of Focus

  • Advanced Statistical Methods — Combine tested techniques with emerging technologies
  • Programming and Technology — Improve familiarity with industry standards software and tools
  • Real-World Problem Solving — Work with real datasets to overcome common challenges and drive decision making
  • Communication and Leadership — Build the professional skill set to present outcomes with confidence and clarity

Applied Statistics
by the Numbers

34 percent
Employment of statisticians is projected to grow by 34 percent from 2016 to 2026, much faster than the average for all occupations.

BLS.gov

 

Learn Advanced Statistical Methods

Michigan Tech’s MS in Applied Statistics online program will help you develop the powerful and practical statistics toolkit necessary to meet the surging worldwide demand for data experts.  Explore the application of advanced statistical methods like predictive modeling, statistical data mining, parametric estimation, model diagnostics, and forecasting. Build on your experience and bachelor’s degree with a graduate education that adds depth and longevity to your career. Benefit from faculty members who are active researchers and bring their expertise to the classroom.

Online Master of Science in Applied Statistics Featured Courses

MA 5701 - STATISTICAL METHODS 3.0 CREDITS

Introduction to design, conduct, and analysis of statistical studies, with an introduction to statistical computing and preparation of statistical reports. Topics include design, descriptive, and graphical methods, probability models, parameter estimation and hypothesis testing.

MA 4720 - DESIGN AND ANALYSIS OF EXPERIMENTS 3.0 CREDITS

Covers construction and analysis of completely randomized, randomized block, incomplete block, Latin squares, factorial, fractional factorial, nested and split-plot designs. Also examines fixed, random and mixed effects models and multiple comparisons and contrasts. The SAS statistical package is an integral part of the course

MA 5761 - COMPUTATIONAL STATISTICS  3.0 CREDITS

Introduction to computationally intensive statistical methods. Topics include simulating random variables from probability distributions, Monte Carlo integration and variance reduction methods, Monte Carlo simulation methods, Bootstrap and jackknife, and permutation tests. This course will use the statistical software R.  

Co-requisite: MA 4770 - Mathematical Statistics II

MA 5781 - TIME SERIES ANALYSIS AND FORECASTING  3.0 CREDITS

Statistical modeling and inference for analyzing experimental data that have been observed at different points in time. Topics include models for stationary and non-stationary time series, model specification, parametric estimation, model diagnostics and forecasting, seasonal models and time series regression models.

MA 5790 - PREDICTIVE MODELING  3.0 CREDITS

Application, construction, and evaluation of statistical models used for prediction and classification. Topics include data pre-processing, over-fitting and model tuning, linear and nonlinear regression models and linear and nonlinear classification models.

Pre-requisite: MA 4710 or MA 4720 or MA 4780

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Michigan Tech is committed to providing career-enhancing online Science, Technology, Engineering, and Mathematics (STEM) programs that combine academic excellence and affordability. As a student, you’ll build off of your existing professional experience and emerge with the specialized knowledge to become an innovator and thought leader in your area of practice.