Experimentation for Improvement (Coursera)

Experimentation for Improvement (Coursera)
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Experimentation for Improvement (Coursera)
We are always using experiments to improve our lives, our community, and our work. Are you doing it efficiently? Or are you (incorrectly) changing one thing at a time and hoping for the best? In this course, you will learn how to plan efficient experiments - testing with many variables. Our goal is to find the best results using only a few experiments. A key part of the course is how to optimize a system.

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We use simple tools: starting with fast hand calculations, then we show how to use FREE software.

The course comes with slides, transcripts of all lectures, subtitles (English & Spanish; some Chinese and French), videos, audio files, source code, and a free textbook. You get to keep all of it, all freely downloadable.

This course is for anyone working in a company, or wanting to make changes to their life, their community, their neighbourhood. You don't need to be a statistician or scientist! There's something for everyone in here.


Syllabus


Week 1

Introduction

We perform experiments all the time, so let's learn some terminology that we will use throughout the course. We show plenty of examples, and see how to analyze an experiment. We end by pointing out: "how not to run an experiment".


Week 2

Analysis of experiments by hand

The focus is on manual calculations. Why? Because you have to understand the most basic building blocks of efficient experiments. We look at systems with 2 and 3 variables (factors). Don't worry; the computer will do the work in the next module.


Week 3

Using computer software to analyse experiments

Now we use free software to do the work for us. You can even run the software through a website (without installing anything special). We look at systems with 2, 3 and 4 factors. Most importantly we focus on the software interpretation.


Week 4

Getting more information, with fewer experiments

This is where the course gets tough and rough, but real. The quiz at the end if a tough one, so take it several times to be sure you have mastered the material - that's all that matters - understanding. We want to do as few experiments as possible, while still learning the most we can. Feel free to skip to module 5, which is the crucial learning from the whole course. You can come back here later. In module


Week 5

Response surface methods (RSM) to optimize any system

This is the goal we've been working towards: how to optimize any system. We start gently. We optimize a system with 1 factor and we also show why optimizing one factor at a time is misleading. We spend several videos to show how to optimize a system with 2 variables.


Week 6

Wrap-up and future directions

We close up the course and point out the next steps you might follow to extend what you have learned here.



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