On Experiments
This work provides incremental improvements in the mathematical formalization of the scientific process, primarily for researchers in automated science and theoretical statistics.
The paper tackles the problem of automating the scientific process by formulating it in a precise mathematical language, resulting in contributions such as a new general data processing inequality and streamlined proofs of key theorems.
The scientific process is a means to turn the results of experiments into knowledge about the world in which we live. Much research effort has been directed toward automating this process. To do this, one needs to formulate the scientific process in a precise mathematical language. This paper outlines one such language. What is presented here is hardly new. The material is based on great thinkers from times past well as more modern contributions. The novel contributions of this paper are: A new general data processing inequality, a bias variance decomposition for canonical losses, streamlined proofs of the Blackwell-Sherman-Stein and Randomization theorems. means of calculating deficiency through linear programming.