Online Applied Statistics Certificate

Transform Complex Data Into Better Decisions.

Applied statistics uses statistical methods to collect, analyze, and interpret data, evaluate uncertainty, and inform decisions. Whether improving manufacturing processes, assessing research findings, or forecasting trends, it turns data into evidence that organizations can use.

Michigan Tech's 9-credit online Graduate Certificate in Applied Statistics combines statistical foundations with practical experience. Designed for working professionals and learners with STEM backgrounds, the program helps you strengthen your analytical skills and apply statistical methods to complex datasets.

Who is This Certificate For?

This certificate is designed for students in STEM disciplines and for working professionals who want stronger statistical and data-analysis skills. It can also benefit people who analyze research results, evaluate processes, interpret complex datasets, or who want to take on more data-focused responsibilities.

What You'll Study

In the Online Applied Statistics certificate, you'll build your understanding of statistical methods, computing, and data analysis while learning to choose appropriate techniques, interpret results, and communicate findings. You'll complete one required course and select two electives.

Skills You'll Gain

Statistical methods: Select techniques, evaluate hypotheses, and draw sound conclusions from data.
Statistical computing and reporting: Use tools such as R and SAS to analyze information and communicate results.
Working with real datasets: Prepare and interpret data, address missing values, and recognize patterns and relationships.

Required Course

MA 5701: Statistical Methods. You'll take this foundational, robust course that introduces study design, descriptive statistics, probability models, estimation, hypothesis testing, statistical computing, and reporting. Then, you will choose two electives from the list below to customize your certificate for your personal and professional needs.

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
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
Pre-Requisite(s): MA 2710 or MA 2720 or MA 3710 or MA 3715 or MA 5701

MA 5750 - Statistical Genetics

Application of statistical methods to solve problems in genetics such as locating genes. Topics include basic concepts of genetics, linkage analysis and association studies of family data, association tests based on population samples (for both qualitative and quantitative traits), gene mapping methods based on family data and population samples.

Credits: 3.0
Lec-Rec-Lab: (0-3-0)
Semesters Offered: Spring, in odd years

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 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)

MA 5791 - Categorical Data Analysis

Structure of 2-way contingency tables. Goodness-of-fit tests and Fisher's exact test for categorical data. Fitting models, including logistic regression, logit models, probit and extreme value models for binary response variables. Building and applying log linear models for contingency tables.

Credits: 3.0
Lec-Rec-Lab: (0-3-0)
Semesters Offered: Spring, in odd years

Why Michigan Tech?

Michigan Tech's unique applied statistics program combines graduate-level study with an accelerated online format designed for working professionals.

Applied Stats students working on a problem while sitting around a table.

Seven-week courses: Make faster progress in focused, accelerated terms.
Flexible start options: Begin in fall, spring, or summer.
Choice of electives: Shape the certificate to align with your professional interests
Reduced tuition opportunities: Eligible military, AmeriCorps, and Peace Corps personnel may qualify for the National Graduate Service Reduced Tuition Rate.
More options: Earn the certificate along or apply the credits to Michigan Tech's Online Master of Science in Applied Statistics.

Three icons (computer, calendar, and diploma).

Where You'll Apply Your Skills

Statistical methods inform decisions in manufacturing, engineering, healthcare, research, environmental science, business, and government. Professionals use them to evaluate experiments, improve processes, forecast trends, measure performance, and assess risk.

Whether you're expanding your responsibilities in a current position or preparing for more data-focused work, advanced statistical skills can help you contribute to decisions grounded in evidence.

And you'll get paid well, too. According to the U.S. Bureau of Labor Statistics (2025), the median annual salary for mathematicians and statisticians is $$105,650.

Get Started on Your Online Certificate in Applied Statistics!

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. Reach out soon or start our fast, free application.