1959-schlaifer-probabilitystatisticsbusinessdecisions.pdf: “Probability and Statistics for Business Decisions: An Introduction to Managerial Economics Under Uncertainty”, (1959; ):
This book is a non-mathematical introduction to the logical analysis of practical business problems in which a decision must be reached under uncertainty. The analysis which it recommends is based on the modern theory of utility and what has come to be known as the “’personal”’ definition of probability; the author believes, in other words, that when the consequences of various possible courses of action depend on some unpredictable event, the practical way of choosing the “best” act is to assign values to consequences and probabilities to events and then to select the act with the highest expected value. In the author’s experience, thoughtful businessmen intuitively apply exactly this kind of analysis in problems which are simple enough to allow of purely intuitive analysis; and he believes that they will readily accept its formalization once the essential logic of this formalization is presented in a way which can be comprehended by an intelligent layman. Excellent books on the pure mathematical theory of decision under uncertainty already exist; the present text is an endeavor to show how formal analysis of practical decision problems can be made to pay its way.
From the point of view taken in this book, there is no real difference between a “statistical” decision problem in which a part of the available evidence happens to come from a ‘sample’ and a problem in which all the evidence is of a less formal nature. Both kinds of problems are analyzed by use of the same basic principles; and one of the resulting advantages is that it becomes possible to avoid having to assert that nothing useful can be said about a sample which contains an unknown amount of bias while at the same time having to admit that in most practical situations it is totally impossible to draw a sample which does not contain an unknown amount of bias. In the same way and for the same reason there is no real difference between a decision problem in which the long-run-average demand for some commodity is known with certainty and one in which it is not; and not the least of the advantages which result from recognizing this fact is that it becomes possible to analyze a problem of inventory control without having to pretend that a finite amount of experience can ever give anyone perfect knowledge of long-run-average demand. The author is quite ready to admit that in some situations it may be difficult for the businessman to assess the numerical probabilities and utilities which are required for the kind of analysis recommended in this book, but he is confident that the businessman who really tries to make a reasoned analysis of a difficult decision problem will find it far easier to do this than to make a direct determination of, say, the correct risk premium to add to the pure cost of capital or of the correct level at which to conduct a test of statistical-significance.
In sum, the author believes that the modern theories of utility and personal probability have at last made it possible to develop a really complete theory to guide the making of managerial decisions—a theory into which the traditional disciplines of statistics and economics under certainty and the collection of miscellaneous techniques taught under the name of operations research will all enter as constituent parts. He hopes, therefore, that the present book will be of interest and value not only to students and practitioners of inventory control, quality control, marketing research, and other specific business functions but also to students of business and businessmen who are interested in the basic principles of managerial economics and to students of economics who are interested in the theory of the firm. Even the teacher of a course in mathematical decision theory who wishes to include applications as well as complete-class and existence theory may find the book useful as a source of examples of the practical decision problems which do arise in the real world.
1961-raiffa-appliedstatisticaldecisiontheory.pdf: “Applied Statistical Decision Theory”, Howard Raiffa, Robert Schlaifer