STATISTICS FROM A TO Z<br />-- CONFUSING CONCEPTS CLARIFIED
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Statistics Tip of the Week: Designed Experiments provide strong evidence of cause and effect.

5/25/2017

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 For a Process output, y, which is a function of several Factors (x's), that is, for
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the Design of Experiments (DOE) discipline can design the most efficient and 
effective experiments to determine the values of the x's which produce the optimal value for -- or the minimal Variation in -- the Response Variable, y.
 
DOE is active and controlling. (This can be done with Processes, but usually not with Populations).
 DOE doesn’t collect or measure existing data with pre-existing values for y and the x’s. DOE specifies Combinations of values for inputs (Factors) and then measures the resulting values of the outputs (Responses). This is the Design of the Experiment.
​

Statistical software packages perform DOE calculations which specify the elements which make up the Design:
  • Levels (e.g., high and low values) of the x Variables
  • Combinations of variables and values
  • Replications
  • Order
Designed Experiments (those designed by DOE) provide much stronger evidence of Cause and Effect than Inferential Statistics. If a Regression Model is to be a valid model of Cause and Effect, it must be able to predict future data derived from controlled experiments. Experiments designed by DOE are a good way to test this. 
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    Andrew A. (Andy) Jawlik is the author of the book, Statistics from A to Z -- Confusing Concepts Clarified, published by Wiley.

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  • Home
    • Why This Book Is Needed
    • Articles List, Additional Concepts
    • Examples: 1-Page Summaries
    • Examples: Concept Flow Diagram
    • Examples: Compare and Contrast Tables
    • Examples: Cartoons
    • Example: Which to Use When Article
  • Buy
  • Blog
  • Sample Articles
  • Videos
  • Author
  • Communicate
  • Files
  • Errata