Design of experiments
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The first statistician to consider a methodology for the design of experiments was Sir Ronald A. Fisher. He described how to test the hypothesis that a certain lady could distinguish by flavor alone whether the milk or the tea was first placed in the cup. While this sounds like a frivolous application, it allowed him to illustrate the most important means of experimental design:
- Randomization
- Replication
- Blocking
- Orthogonality
- use of factorial experiments instead of the one-factor-at-a-time method
In 1950, Gertrude Mary Cox and William Cochran published the book Experimental Design which became the major reference work on the design of experiments for statisticians for years afterwards.
Developments of the theory of linear models have encompassed and surpassed the cases that concerned early writers. Today, the theory rests on advanced topics in abstract algebra and combinatorics.
As with all other branches of statistics, there is both classical and Bayesian experimental design.
See also
- planning statistical research
- survey sampling
- independent variable
- dependent variable
- randomized controlled trial
- statistics
- statistical theory
External links
- [Biography of R. A. Fisher]
- [Description of how to design experiments]
- A [chapter] from a [handbook on engineering statistics] at NIST
- [Articles on Design of Experiments]
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