Walter A. Shewhart

Walter A. Shewhart (1931). Economic Control of Quality of Manufactured Product.

• Broadly speaking, the object of industry is to set up economic ways and means of satisfying human wants and in so doing to reduce everything possible to routines requiring a minimum amount of human effort.
  • p. vii

• Progress in modifying our concept of control has been and will be comparatively slow. In the first place, it requires the application of certain modern physical concepts; and in the second place it requires the application of statistical methods which up to the present time have been for the most part left undisturbed in the journal in which they appeared.
  • p. 4-5

• Postulate 1. All chance systems of causes are not alike in the sense that they enable us to predict the future in terms of the past.

Postulate 2. Constant systems of chance causes do exist in nature.

Postulate 3. Assignable causes of variation may be found and eliminated.

• p. 8

• In other words, the fact that the criterion we happen to use has a fine ancestry of highbrow statistical theorems does not justify its use. Such justification must come from empirical evidence that it works.
  • p. 18

• Based upon evidence such as already presented, it appears feasible to set up criteria by which to determine when assignable causes of variation in quality have been eliminated so that the product may then be considered to be controlled within limits. This state of control appears to be, in general, a kind of limit to which we may expect to go economically in finding and removing causes of variability without changing a major portion of the manufacturing process as, for example, would be involved in the substitution of new materials or designs.
  • p. 24

• The definition of random in terms of a physical operation is notoriously without effect on the mathematical operations of statistical theory because so far as these mathematical operations are concerned random is purely and simply an undefined term. The formal and abstract mathematical theory has an independent and sometimes lonely existence of its own. But when an undefined mathematical term such as random is given a definite operational meaning in physical terms, it takes on empirical and practical significance. Every mathematical theorem involving this mathematically undefined concept can then be given the following predictive form: If you do so and so, then such and such will happen.
  • Shewhart, Walter A.; Deming, William E. (1939). Statistical Method from the Viewpoint of Quality Control. The Graduate School, The Department of Agriculture. p. 18. 

• Rule 1. Original data should be presented in a way that will preserve the evidence in the original data for all the predictions assumed to be useful.
• Rule 2. Any summary of a distribution of numbers in terms of symmetric functions should not give an objective degree of belief in any one of the inferences or predictions to be made therefrom that would cause human action significantly different from what this action would be if the original distributions had been taken as evidence.
  • Shewhart, Walter A.; Deming, William E. (1939). Statistical Method from the Viewpoint of Quality Control. The Graduate School, The Department of Agriculture. p. 88. 

Walter A. Shewhart, and William E. Deming, (1939). Statistical Method from the Viewpoint of Quality Control. The Graduate School, The Department of Agriculture. p. 18.

• Every sentence in order to have definite scientific meaning must be practically or at least theoretically verifiable as either true or false upon the basis of experimental measurements either practically or theoretically obtainable by carrying out a definite and previously specified operation in the future. The meaning of such a sentence is the method of its verification.
  • p. 94

• Both pure and applied science have gradually pushed further and further the requirements for accuracy and precision. However, applied science, particularly in the mass production of interchangeable parts, is even more exacting than pure science in certain matters of accuracy and precision.
  • p. 120