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Factorial and Fractional Factorial Designs
  • Level Professional
  • Duration 12 hours
  • Course by Arizona State University
  • Offered by

About

Many experiments in engineering, science and business involve several factors. This course is an introduction to these types of multifactor experiments. The appropriate experimental strategy for these situations is based on the factorial design, a type of experiment where factors are varied together. This course focuses on designing these types of experiments and on using the ANOVA for analyzing the resulting data. These types of experiments often include nuisance factors, and the blocking principle can be used in factorial designs to handle these situations. As the number of factors of interest grows full factorials become too expensive and fractional versions of the factorial design are useful. This course will cover the benefits of fractional factorials, along with methods for constructing and analyzing the data from these experiments.

Modules

Welcome

    • 2 Videos
    • 4 Readings
    • 1 Discussion
    • 1 ExternalTool
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1 External Tool

  • JMP Virtual Lab

1 Discussions

  • Meet the class

2 Videos

  • Instructor Welcome
  • Course Introduction

4 Readings

  • Course Description
  • Course Textbook and Resources
  • Best Practices in Online Learning (or How to Succeed in This Class)
  • Project

Introduction to Factorial Design

    • 7 Videos
    • 1 Readings
    • 2 Assignment
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2 Assignment

  • Unit 1: Concept Questions
  • Exercise 1

7 Videos

  • Introduction to Factorials
  • The Battery Life Experiment
  • Choice of Sample Size
  • Factorials with More Than Two Factors
  • Battery Life Example
  • Tool Life Example
  • Target Detection Example

1 Readings

  • Unit 1: Introduction

The 2^k Factorial Design

    • 12 Videos
    • 1 Readings
    • 2 Assignment
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2 Assignment

  • Unit 2: Concept Questions
  • Exercise 2

12 Videos

  • Analysis Procedure for a Factorial Design
  • Reduced Model
  • How Much Replication is Necessary?
  • ANOVA Summary - Full Model
  • The General 2^k Factorial Design
  • Estimates of the Effects
  • Other Methods for Analyzing Unpredicated Factorials
  • Outliers
  • The 2^k design and design optimality
  • Addition of Center Points to a 2^k Design
  • Plasma Etching Example
  • Filtration Rate Example

1 Readings

  • Unit 2: Introduction

Blocking and Confounding in the 2^k Factorial Design

    • 4 Videos
    • 1 Readings
    • 2 Assignment
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2 Assignment

  • Unit 3: Concept Questions
  • Exercise 3

4 Videos

  • Blocking a Replicated Design
  • Confounding in Blocks
  • Confounding in Blocks, Pt. 2
  • Filtration Rate with Blocking Example

1 Readings

  • Unit 3: Introduction

Two-Level Fractional Factorial Designs

    • 9 Videos
    • 1 Readings
    • 1 PeerReview
    • 2 Assignment
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2 Assignment

  • Unit 4: Concept Questions
  • Exercise 4

1 Peer Review

  • Project Report

9 Videos

  • Why do Fractional Factorial Designs Work?
  • Construction of a One-half Fraction
  • The General 2^(k-p) Fractional Factorial Design
  • Alias Structures in Fractional Factorials and Other Designs
  • Resolution III Designs
  • Plackett-Burman Designs
  • Resolution IV and V Designs
  • Filtration Rate Fractional Factorial Example
  • Eye Focus Time Example

1 Readings

  • Unit 4: Introduction

Auto Summary

Explore the essentials of multifactor experiments in engineering, science, and business with "Factorial and Fractional Factorial Designs." This professional-level course, offered by Coursera, delves into experimental design strategies, including factorial and fractional factorial designs, and ANOVA analysis. Over 720 minutes, learn to handle nuisance factors with blocking principles and construct cost-effective fractional factorials. Suitable for professionals seeking advanced expertise, this course is available through Starter and Professional subscription options.

Douglas C. Montgomery
Instructor

Douglas C. Montgomery