Database Cardinality: A Brief Overview
April 5, 2024
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Design, Develop and Improve Products and Processes. Be able to apply modern experimental techniques to improve existing products and processes and bring new products and processes to market faster
Instructor: Douglas C. Montgomery
12,899 already enrolled
Included with
(315 reviews)
Recommended experience
Beginner level
A previous course in basic statistical methods. The required background is introduced and reviewed as needed throughout the course.
(315 reviews)
Recommended experience
Beginner level
A previous course in basic statistical methods. The required background is introduced and reviewed as needed throughout the course.
Plan, design and conduct experiments efficiently and effectively, and analyze the resulting data to obtain valid objective conclusions.
Use response surface methods for system optimization as a follow-up to successful screening.
Use experimental design tools for computer experiments, both deterministic and stochastic computer models.
Use software tools to create custom designs based on optimal design methodology for situations where standard designs are not easily applicable.
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Learn modern experimental strategy, including factorial and fractional factorial experimental designs, designs for screening many factors, designs for optimization experiments, and designs for complex experiments such as those with hard-to-change factors and unusual responses. There is thorough coverage of modern data analysis techniques for experimental design, including software. Applications include electronics and semiconductors, automotive and aerospace, chemical and process industries, pharmaceutical and bio-pharm, medical devices, and many others.
You can see an overview of the specialization from Dr. Montgomery here.
Applied Learning Project
Participants will complete a project that is typically based around their own work environment, and can use this to effectively demonstrate the application of experimental design methodology. The structure of the course and the step-by-stem process taught in the course is designed to ensure participant success.
By the end of this course, you will be able to:
Approach complex industrial and business research problems and address them through a rigorous, statistically sound experimental strategy
Use modern software to effectively plan experiments
Analyze the resulting data of an experiment, and communicate the results effectively to decision-makers.
Conduct a factorial experiment in blocks and construct and analyze a fractional factorial design
Apply the factorial concept to experiments with several factors
Use the analysis of variance for factorial designs
Use the 2^k system of factorial designs
Conduct experiments w/computer models and understand how least squares regression is used to build an empirical model from experimental design data
Understand the response surface methodology strategy to conduct experiments where system optimization is the objective
Recognize how the response surface approach can be used for experiments where the factors are the components of a mixture
Recognize where the objective of the experiment is to minimize the variability transmitted into the response from uncontrollable factors
Design and analyze experiments where some of the factors are random
Design and analyze experiments where there are nested factors or hard-to-change factors
Analyze experiments with covariates
Design and analyze experiments with nonnormal response distributions
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There are 15 modules, spread across 4 courses. Each module is based on one chapter of the textbook. The specialization can be completed in approximately 4 months.
Knowledge of basic statistical methods, although the background knowledge is introduced and reviewed throughout the course as needed.
It is not necessary to take the courses in a specific order, but we recommend taking the courses in the order presented, as each subsequent course will build on material from previous courses.
Coursera courses and certificates don't carry university credit, though some universities may choose to accept them for credit.
Design efficient and effective experiments to solve a wide variety of problems in science, engineering, and business where data collection and analysis is essential to success.
This course is completely online, so there’s no need to show up to a classroom in person. You can access your lectures, readings and assignments anytime and anywhere via the web or your mobile device.
If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.
Yes! To get started, click the course card that interests you and enroll. You can enroll and complete the course to earn a shareable certificate, or you can audit it to view the course materials for free. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. Visit your learner dashboard to track your progress.
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. If you only want to read and view the course content, you can audit the course for free. If you cannot afford the fee, you can apply for financial aid.
Financial aid available,