Unsolved Problems of Experimental Statistics

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Abstract
The author shows how these problems are generated naturally as a consequence of the following hypergeneral principles: (1) Different ends require different means and different logical structures. (2) In each area, statistical method must and does evolve, mainly by adding both immediate ends and considerations. (3) While techniques are important in experimental statistics, knowing when to use them and why to use them are more important. (4) In the long run, it does not pay a statistician to fool either himself or his clients. Each of these is then broken down into 4 or 5 general principles which are illustrated by the discussion of particular problems. Finally, 51 specific questions are stated which imply many, but not all, of the existing unsolved problems.

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