Resources for Designed Experiments course, Experimentation for Improvement, on Coursera

This list of resources will be updated over time. To make a suggestion for adding to this list, please post a message here with your suggestion, even after you have completed the course.

Software tools for this course

• The R software package used in this course requires a 2-step installation:

1. Download and install the base R language, http://yint.org/R (you don't use this download directly, but it is required for the next step below)
2. Download and install RStudio [free!], http://yint.org/RStudio (you use this software with the videos)

• Do you need a quick introduction to R? Try this free course out: http://yint.org/Rcourse

Downloadable resources for this course

* Please note: the server will block you if you download too many files too quickly. Please respect the fact that others are also accessing the resources at the same time.

In all the hyperlinks below replace "xx" with the module number. These are all the modules:

1A, 1B, 1C, 1D, 2A, 2B, 2C, 2D, 3A, 3B, 3C, 3D, 4A, 4B, 4C, 4D, 4E, 4F, 4G, 4H, 5A, 5B, 5C, 5D, 5E, 5F, 5G, 6.  [it is case-sensitive!]

• All scripts: https://yint.org/scripts/xx (for example  https://yint.org/scripts/1B)

• Access all of the scripts from this link 

• All slides: https://yint.org/pdfs/xx.pdf (for example https://yint.org/pdf/1B.pdf)
• All videos: https://yint.org/media/xx.mp4 (for example https://yint.org/media/1B.mp4)
• All audio: https://yint.org/media/xx.mp3 (for example https://yint.org/media/1B.mp3)

The videos are also part of this YouTube playlist: https://www.youtube.com/playlist?list=PLHUnYbefLmeOPRuT1sukKmRyOVd4WSxJE

Note that the above video/course resources are provided to you under the Creative Commons Attribution-ShareAlike 4.0 Unported (CC BY-SA 4.0) licence.

Online comprehensive references/tutorials/guides on Designed Experiments

• StatSoft, Design of Experiments: Science, Industrial DOE
• A tutorial from MoreStream.com
• An online resource from PennState about Design of Experiments
• The NIST guide to experiments (see these 3 cases studies, in particular the one on RSM)
• Another Coursera MOOC on experiments, in the Social Sciences: https://www.coursera.org/learn/quantitative-methods (talks about the fundamental reasons behind experiments)

Textbooks

• Box, Hunter and Hunter, "Statistics for Experimenters", 2nd edition (the 1st edition is also very good)
• An extremely comprehensive textbook on DoE, covering systems will multiple levels (2, 3, and more), RSM with many factors:  Owen L. Davies, "The Design and Analysis of Industrial Experiments"
• Response Surface Methods textbook by Box and Draper, 2nd edition, "Response Surfaces, Mixtures, and Ridge Analyses"
• Another textbook on Response Surface Methodology, by Myers, Montgomery and Anderson-Cook
• A pre-print of a complete textbook related to Designed Experiments, "Design of Comparative Experiments" by R.A. Bailey
• The book by Goos and Jones, Optimal Design of Experiments, and also two short YouTube videos: video 1, video 2.
• Schmidt, S.R. and Launsby, R.G. "Understanding Industrial Designed Experiments"
• Kevin Dunn, Process Improvement using Data (chapter 5) [this is the course textbook for this MOOC].

Specific topics

• How the trade-off table is constructed [paywall]
• A review of Evolutionary Operation, by Hunter and Kittrell, 1966 [paywall]