Experimental Design Basics
Learn statistical methods for planning, conducting, and analyzing experiments efficiently. Master DOE principles for industrial applications.
Learn statistical methods for planning, conducting, and analyzing experiments efficiently. Master DOE principles for industrial applications.
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Design of Experiments Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
4.7
(271 ratings)
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What you'll learn
Plan and conduct efficient experimental designs
Use modern software for experimental planning
Analyze experimental data effectively
Communicate results to decision-makers
Apply statistical methods for process improvement
Skills you'll gain
This course includes:
4.7 Hours PreRecorded video
7 quizzes
Access on Mobile, Tablet, Desktop
FullTime access
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There are 5 modules in this course
This comprehensive course teaches the fundamentals of designing and analyzing experiments for industrial and business applications. Students learn to plan efficient experiments, use statistical methods for data analysis, and make objective conclusions. The course covers essential topics including comparative experiments, analysis of variance (ANOVA), randomized blocks, and Latin squares. Through practical examples and software applications using JMP, Design-Expert, and Minitab, students develop skills in experimental design that can be applied across various industrial settings.
Getting Started and Introduction to Design and Analysis of Experiments
Module 1 · 3 Hours to complete
Simple Comparative Experiments
Module 2 · 3 Hours to complete
Experiments with a Single Factor - The Analysis of Variance
Module 3 · 2 Hours to complete
Randomized Blocks, Latin Squares, and Related Designs
Module 4 · 2 Hours to complete
Project
Module 5 · 1 Hours to complete
Fee Structure
Instructor
Pioneering Expert in Industrial Engineering and Statistics
Douglas C. Montgomery serves as the Regents' Professor of Industrial Engineering and the ASU Foundation Professor of Engineering at Arizona State University. With a distinguished academic career, he previously held prominent positions at the University of Washington and Georgia Institute of Technology. Dr. Montgomery earned his BSIE, MS, and Ph.D. degrees from Virginia Tech and has extensive industrial experience with companies such as Union Carbide Corporation and Eli Lilly. His research primarily focuses on industrial statistics, including design of experiments, quality and reliability engineering, and time series analysis. A prolific author, he has written thirteen influential books and over 275 journal articles, contributing significantly to the fields of statistical methodology and engineering practices. Dr. Montgomery's expertise has been recognized through numerous awards, including the Shewhart Medal and the George Box Medal. As a mentor, he has supervised 69 doctoral dissertations and continues to impact the next generation of engineers through his teaching and research initiatives. His commitment to advancing industrial statistics positions him as a leading figure in engineering education and practice.
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4.7 course rating
271 ratings
Frequently asked questions
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