Arizona State University
Design of Experiments Specialization
Arizona State University

Design of Experiments Specialization

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

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4.7

(317 reviews)

Beginner level

Recommended experience

1 month
at 10 hours a week
Flexible schedule
Learn at your own pace
Get in-depth knowledge of a subject
4.7

(317 reviews)

Beginner level

Recommended experience

1 month
at 10 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • 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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Taught in English

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Specialization - 4 course series

Experimental Design Basics

Course 112 hours4.7 (294 ratings)

What you'll learn

  • 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.

Skills you'll gain

Category: Data Analysis
Category: Quality Control
Category: Descriptive Statistics
Category: Research Design
Category: Variance Analysis
Category: Statistical Hypothesis Testing
Category: statistical Methods for Process and Product improvement
Category: Estimation
Category: Sampling (Statistics)
Category: experiment design
Category: A/B Testing
Category: Experimentation
Category: Sample Size Determination
Category: Statistical Software
Category: Statistical Analysis
Category: designing experiments
Category: Statistical Methods
Category: design of experiments

Factorial and Fractional Factorial Designs

Course 211 hours4.8 (76 ratings)

What you'll learn

  • 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

Skills you'll gain

Category: Data Analysis
Category: Research Design
Category: Experimentation
Category: Statistical Modeling
Category: Variance Analysis
Category: Statistical Analysis
Category: Statistical Methods
Category: Statistics

Response Surfaces, Mixtures, and Model Building

Course 313 hours4.7 (66 ratings)

What you'll learn

  • 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

Skills you'll gain

Category: Data Analysis
Category: Experimentation
Category: Regression Analysis
Category: Mathematical Modeling
Category: Statistical Modeling
Category: Statistical Analysis
Category: Statistical Methods

Random Models, Nested and Split-plot Designs

Course 49 hours4.6 (34 ratings)

What you'll learn

  • 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

Skills you'll gain

Category: Data Analysis
Category: Sampling (Statistics)
Category: Regression Analysis
Category: Probability & Statistics
Category: Probability Distribution
Category: Statistical Modeling
Category: Data Transformation
Category: Statistical Analysis
Category: Statistical Methods

Instructor

Douglas C. Montgomery
Arizona State University
4 Courses24,494 learners

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