Design of Experiments courses can help you learn statistical methods, experimental design principles, and data analysis techniques. You can build skills in hypothesis testing, factor analysis, and interpreting results to make informed decisions. Many courses introduce tools like R, Python, and specialized software for conducting experiments, enabling you to apply these skills in various fields such as agriculture, manufacturing, and healthcare.

Arizona State University
Skills you'll gain: Experimentation, Sample Size Determination, Research Design, Regression Analysis, Statistical Analysis, Statistical Methods, Data Analysis Software, Statistical Modeling, Statistical Hypothesis Testing, Design Strategies, Sampling (Statistics), Probability & Statistics, Mathematical Modeling, Analysis, Model Evaluation, Data Transformation, Descriptive Statistics, Probability Distribution, Variance Analysis, Data Analysis
Beginner · Specialization · 3 - 6 Months

Arizona State University
Skills you'll gain: Experimentation, Sample Size Determination, Research Design, Statistical Analysis, Statistical Methods, Data Analysis Software, Statistical Hypothesis Testing, Design Strategies, Probability & Statistics, Statistical Modeling, Descriptive Statistics, Quality Control, Variance Analysis
Intermediate · Course · 1 - 3 Months

Arizona State University
Skills you'll gain: Experimentation, Research Design, Statistical Modeling, Statistical Methods, Applied Machine Learning, Supervised Learning, Logistic Regression, Predictive Modeling, Statistical Programming, Statistical Analysis, Statistical Inference, Simulation and Simulation Software, Probability & Statistics, Data Science, Data Visualization, Simulations, Data Analysis, Data Analysis Software
Intermediate · Course · 1 - 4 Weeks

University of Colorado Boulder
Skills you'll gain: Statistical Hypothesis Testing, Experimentation, Research Design, Statistical Analysis, Data Ethics, Statistical Modeling, Data Science, A/B Testing, Data Analysis, Quantitative Research, Regression Analysis, Statistical Inference, Probability & Statistics, Sample Size Determination, Linear Algebra, Calculus
Build toward a degree
Intermediate · Course · 1 - 4 Weeks
Johns Hopkins University
Skills you'll gain: Clinical Trials, Clinical Research, Clinical Research Ethics, Good Clinical Practices (GCP), Informed Consent, Biostatistics, Healthcare Ethics, Science and Research, Regulatory Compliance
Beginner · Course · 1 - 3 Months

McMaster University
Skills you'll gain: Experimentation, Data Visualization, Predictive Modeling, Pareto Chart, Process Improvement and Optimization, Simulation and Simulation Software, Process Optimization, Statistical Software, R Programming, Data Analysis, Statistical Analysis, R (Software), Case Studies
Intermediate · Course · 1 - 3 Months
University of California San Diego
Skills you'll gain: Design Research, Interaction Design, User Experience Design, Statistical Analysis, Usability, Ideation, User Research, Graphic and Visual Design, User Interface (UI) Design, Experimentation, Prototyping, Usability Testing, Human Centered Design, Human Computer Interaction, A/B Testing, Human Factors, Collaborative Software, Telecommuting, R Programming, Storyboarding
Intermediate · Specialization · 3 - 6 Months

Arizona State University
Skills you'll gain: Experimentation, Statistical Analysis, Statistical Methods, Variance Analysis, Data Analysis, Sample Size Determination, Statistical Modeling
Intermediate · Course · 1 - 4 Weeks

Skills you'll gain: Applied Mathematics, Mathematical Modeling, Matlab, High Voltage, Three-Phase, Electrical Engineering, electromagnetics, Simulation and Simulation Software, Electric Power Systems, Electrical Power, Environmental Science, Environmental Engineering, Design
Intermediate · Course · 1 - 4 Weeks

University of North Texas
Skills you'll gain: Research Design, Research, Research Methodologies, Surveys, Qualitative Research, Scientific Methods, Business Research, Research Reports, Data Collection, Sample Size Determination, Analysis, Ethical Standards And Conduct, Decision Making, Probability & Statistics
Beginner · Course · 1 - 4 Weeks

The State University of New York
Skills you'll gain: Electrical Power, Basic Electrical Systems, Electric Power Systems, Wiring Diagram, Equipment Design, Energy and Utilities, Electronic Components, Sustainable Design, System Requirements, Electrical Safety, Engineering Calculations, Performance Testing, Physical Science, Estimation
Intermediate · Course · 1 - 3 Months

Queen Mary University of London
Skills you'll gain: Research Reports, Statistical Hypothesis Testing, Survey Creation, Research Design, Statistical Analysis, Data Collection, Quantitative Research, Research Methodologies, Data Preprocessing, Probability & Statistics, Descriptive Statistics, Data Literacy
Beginner · Course · 1 - 4 Weeks
Design of experiments (DOE) is a structured method for planning and running tests to understand how different factors affect an outcome. Instead of changing one variable at a time, DOE looks at multiple variables together to see which ones truly matter and how they interact. It’s important because it helps teams optimize processes, improve product quality, and solve problems more efficiently. By relying on data rather than guesswork, organizations can make better decisions, reduce waste, and achieve more reliable results.
A background in design of experiments can open doors to various career opportunities. Potential job titles include data analyst, quality engineer, research scientist, and biostatistician. These roles often involve applying statistical methods to design experiments, analyze data, and interpret results. Industries such as pharmaceuticals, manufacturing, and agriculture frequently seek professionals skilled in DOE to enhance product development and process optimization.
To learn design of experiments effectively, it helps to build a strong foundation in statistics, particularly in core experimental design principles. Familiarity with software tools used for data analysis, such as R or Python, is also beneficial. You’ll also want to understand key concepts like randomization, replication, and factorial designs, which are essential for creating reliable experiments and interpreting results with confidence.
There are several online courses available that can help you learn design of experiments. A highly recommended option is the Design of Experiments Specialization, which covers essential concepts and practical applications. This specialization provides a comprehensive overview, making it suitable for both beginners and those looking to deepen their understanding of DOE.
Yes. You can start learning experiment design skills on Coursera for free in two ways:
If you want to keep learning, earn a certificate in experiment design topics, or unlock full course access after the preview or trial, you can upgrade or apply for financial aid.
To learn design of experiments, begin by taking online courses or workshops that cover statistical methods and experimental design fundamentals. Applying what you learn through practical examples and real-world case studies can help reinforce key concepts. You can also deepen your understanding by joining study groups or online forums, where discussing ideas and challenges with peers can improve both comprehension and retention.
Typical topics covered in design of experiments courses include the principles of experimental design, types of designs (such as factorial and fractional factorial designs), randomization techniques, analysis of variance (ANOVA), and interpretation of results. Courses may also explore real-world applications in various fields, providing learners with practical insights into how DOE is utilized in different industries.
For training and upskilling employees in design of experiments, the Design of Experiments Specialization is an excellent choice. It offers a structured curriculum that can help teams understand the fundamentals of DOE and apply them effectively in their work. This specialization can enhance employees' analytical skills and improve their ability to contribute to data-driven decision-making processes.