Online Masters of Applied Statistics (MS) | Michigan Tech Global Campus

Solve Real-World Problems With Applied Statistics.

Applied statistics is the implementation of statistical methods, techniques, and theories to real-world problems and situations in several disciplines, such as science, engineering, business, medicine, social sciences, and more. This important discipline involves collecting, summarizing, analyzing, interpreting, and presenting data to make informed decisions, solve problems, and answer questions.

Applied statisticians also use advanced techniques, such as machine learning algorithms, to extract insights and patterns from large datasets. Experts in applied statistics work in several settings: research institutions, the government, business and finance, universities, healthcare systems, and more.

With Michigan Tech's Online MS in Applied Statistics, you, too, can build the specialized skills to meet the growing demand for statistics and data professionals. MTU's distance-learning, research-based MS combines tested techniques with emerging technologies while maintaining the high standards of a Michigan Tech graduate education.

Get the Details About This Program!

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Take Foundational, Rigorous Applied Statistics Courses.

The online MSAS curriculum is based on direct industry feedback. Through in-depth coursework, you will learn how to merge theory and application, enabling you to graduate ready to address the data-driven challenges that public, private, and non-governmental institutions face.

You'll develop expertise in several programming languages and tools that applied statisticians regularly use on the job.

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Our compact, 7-week courses are periodically offered throughout the year. Depending on what courses you take, the availability of those courses, and how many courses you complete in a semester, you may be able to earn your graduate degree quickly. That is, if you took two courses per semester, you could earn your MS in five semesters.

But before making your plan, please check the courses and registration page to see what courses are currently running.

Whatever courses you decide upon, you'll be taught by expert faculty from the Department of Mathematical Sciences who conduct research on the most effective mathematical and statistical approaches to diverse problems. You'll receive the same quality instruction as do students in MTU's on-site classes.

Need to brush up on your Linear Algebra? No problem. MTU offers an affordable Linear Algebra Bridge Course for those who want to apply to (or are provisionally accepted into) the Online MSAS degree.

Explore the Curriculum of the Online MSAS.

MA 4700 - Probability and Statistical Inference I

Introduction to probabilistic methods. Topics include probability laws, counting rules, discrete and continuous random variables, moment generating functions, expectation, joint distributions, and the Central Unit Theorem.

Credits: 3.0
Lec-Rec-Lab: (0-3-0)
Semesters Offered: Fall, Spring, Summer
Restrictions: Permission of department required
Pre-Requisite(s): MA 3160 and (MA 2710 or MA 2720 or MA 3710 or MA 3715)

MA 4705 - Probability and Statistical Inference II

Topics include sampling distributions, theory of point and interval estimation, properties of estimators, and theory of hypothesis testing.

Credits: 3.0
Lec-Rec-Lab: (0-3-0)
Semesters Offered: On Demand
Restrictions: Permission of department required
Pre-Requisite(s): MA 4700

MA 4710 - Regression Analysis

Covers simple, multiple, and polynomial regression; estimation, testing, and prediction; weighted least squares, matrix approach, dummy variables, multicollinearity, model diagnostics and variable selection. A statistical computing package is an integral part of the course. Some prior experience with R is expected.

Credits: 3.0
Lec-Rec-Lab: (0-3-0)
Semesters Offered: Fall, Summer
Pre-Requisite(s): MA 2710 or MA 2720 or MA 3710 or MA 3715 or MA 5701

MA 4720 - Design and Analysis of Experiments

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 R programming language is an integral part of the course.

Credits: 3.0
Lec-Rec-Lab: (0-3-0)
Semesters Offered: Spring, Summer
Pre-Requisite(s): MA 2710 or MA 2720 or MA 3710 or MA 3715 or MA 5701

MA 5701 - Statistical Methods

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.

Credits: 3.0
Lec-Rec-Lab: (0-3-0)
Semesters Offered: Fall, Spring, Summer
Restrictions: Must be enrolled in one of the following Level(s): Graduate

MA 5751 - Statistical Data Mining

Course will cover various topics in statistical data mining, including linear model selection and regularization, regression and smoothing splines, unsupervised learning, resampling methods, tree-based methods, and deep learning. This course will introduce modern statistical data mining techniques and their applications.

Credits: 3.0
Lec-Rec-Lab: (0-3-0)
Semesters Offered: Spring, in odd years
Pre-Requisite(s): (MA 4700 or MA 4760) and (MA 5701 or MA 4710)

MA 5761 - Computational Statistics

Introduction to computationally intensive statistical methods. Topics include resampling methods, Monte Carlo simulation methods, smoothing technique to estimate functions, and methods to explore data structure. This course will use the statistical software R.

Credits: 3.0
Lec-Rec-Lab: (0-3-0)
Semesters Offered: Fall
Pre-Requisite(s): MA 4770(C) or (MA 4700 and MA 5701)

MA 5771 - Applied Generalized Linear Models

Construction, evaluation, and application of generalized linear models to analyze different types of data. Topics include logistic and Poisson regression, multinomial logit models, random effects and mixed effect models, models for repeated measures and longitudinal data. Introduce theory on GLM fitting, hypothesis testing, and diagnostic models.

Credits: 3.0
Lec-Rec-Lab: (0-3-0)
Semesters Offered: On Demand
Pre-Requisite(s): MA 4710 and (MA 4760 or (MA 4700 and MA 5701))

MA 5781 - Time Series Analysis and Forecasting

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.

Credits: 3.0
Lec-Rec-Lab: (0-3-0)
Semesters Offered: Spring
Pre-Requisite(s): (MA 2710 or MA 2720 or MA 3710 or MA 3715 or MA 5701) and (MA 3720 or EE 3180 or MA 4700)

MA 5790 - Predictive Modeling

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.

Credits: 3.0
Lec-Rec-Lab: (0-3-0)
Semesters Offered: Fall, Spring
Pre-Requisite(s): MA 3740 or MA 4710 or MA 4720 or MA 4780 or (MA 4700 and MA 5701)

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Read What Previous Graduates Have Said.

"I chose Michigan Tech because I am a high school math teacher and I was looking for a program in statistics that was 100% online. I was aware of Michigan Tech's reputation and knew they were a solid school in mathematical fields. I also like that no GRE was required for admission."Mary Lonz, High School Math Teacher, MS in Applied Statistics

"The fact that the courses cover multiple applications is what stood out to me. It shows MTU has done adequate research to ensure students succeed post their degree. The professors provide feedback to our discussion posts in a timely manner. I feel they are there for you whenever you need them."Jay Huen Lee, Senior Analyst/Commercial Analytics, MS in Applied Statistics

Get Applied Statistics Skills for Several Rewarding Careers.

With MTU's Online MS in Applied Statistics, you'll develop skills for a wide range of industries and sectors where data analysis and statistical methods are implemented to make decisions, solve problems, and improve processes. Some common areas where applied statisticians find employment include the following:

Man explaining applied statistics on a monitor.

Three applied statistics professionals solving a problem on a board.

Healthcare: Applied statisticians work in hospitals, research institutions, pharmaceutical companies, and health agencies to analyze clinical trials, epidemiological studies, patient data, and health outcomes.
Finance: Experts in applied statistics work at banks, investment firms, insurance companies, and hedge funds to analyze financial data, build predictive models, optimize portfolios, and detect fraud.
Government Agencies: Local, state, and national government agencies employ applied statisticians to analyze census data, economic indicators, public health data, crime statistics, and more.
Marketing: In market research firms and departments, applied statisticians analyze consumer data, conduct surveys, as well as evaluate trends and consumer behavior.
Technology: Applied statisticians are employed in companies that are developing software, internet services, and data analytics platforms. Here, they analyze user behavior, optimize algorithms, and improve products.
Manufacturing: Applied statisticians aid in monitoring production processes, analyzing quality control data, identifying defects, and improving product quality and efficiency.
Environmental Science: Here, they analyze ecological data, climate models, and environmental monitoring data to study biodiversity, ecosystem dynamics, and the impacts of human activities on the environment.

Get Started on Your Online MS in Applied Statistics!

Enhance your career options by earning an online master's degree in applied statistics. Employers recognize advanced training—a master's degree may qualify you for leadership opportunities, project management responsibilities, or the chance to work on more complicated or sophisticated projects.

Take the next steps on your online educational journey at Michigan Tech. We are here to answer your questions and to help you succeed in your online program.

Online Master of Science in Applied Statistics (MS)