Lesson 5: Design of Experiments: Build Linear Models.
Mukul Mehta, Cleveland, Ohio
In the previous lesson, we talked about Planning Experiments. Let's move forward.
Here is the key question: How do we analyze experimental data quickly and effectively? How do we develop a generalized approach that works for most of our product development and process improvement problems?
The answer: Build Linear Models.
Linear models are simple and smart.
A linear model is a very good general purpose powerful, yet simple solution:
A linear model is a good solution because:
- It is simple - it has fewer parameters.
- It is easy to build.
- It is easy to use.
- It is scalable; it can be applied to small problems involving a few variables; or, it can be easily applied to BIG problems with a large number of variables.
- It is easy to understand.
- It is theoretically sound.
- It has predictive power.
- It provides us with x-ray vision.
As Einstein said, "Everything should be made as simple as possible, but not simpler." A linear model is a good example of that.
For almost all your projects, you can start with linear models.
To read the rest of the tutorial sign up at www.DesignOfExperiments.co.in
Take care.
Mukul Mehta
Mukul Mehta & Associates
25797 Briarwood Court
Cleveland, Ohio, 44145 USA
Phone: 440-808-6700 Fax: 440-808-6767
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