Decision-Making under Uncertainty: An Applied Statistics Approach

Decision-Making under Uncertainty: An Applied Statistics Approach

Decision-Making under Uncertainty: An Applied Statistics Approach

Decision-Making under Uncertainty: An Applied Statistics Approach

Synopsis

In this thorough volume Chacko undertakes the analysis of 24 real-life decision-making situations, both those with few data points (e.g., Cuban Missile Crisis), and many data points (e.g., aspirin for heart attack). These situations encompass decision-making in a variety of business, social and political, physical and biological, and military environments. Though different, all have one characteristic in common: their outcomes are uncertain/unknown, and unknowable. Chacko demonstrates how the decision-maker can reduce uncertainty by choosing probable outcomes using the statistical methods he introduces.

Excerpt

This work focuses on the use of incomplete data for irrevocable commitment of resources in business, social and political, physical and biological, and military environments. The 24 real-life and real-to-life applications motivate the selection of appropriate concepts and computations to solve problems and make decisions. The applications are grouped by area: market (9), social and political (7), physical and biological (5), and military (3), as shown in Figure P.1.

The schematic at the beginning of each part of the book shows "Decision- making" in tier 1, leading to the combination of Decision-Makers (single, multiple) and Decision-Variables (single, multiple) in tier 2. The three elements critical to decision-making--(1) Outcome, (2) Probability, and (3) Attitude--appear in tier 3.

Part I discusses several one-of-a-kind decision situations. The schematic presents "Single Decision-Maker (DM), Single Variable" as the primary theme. Chapter 1 opens with the bone-chilling choices faced by the North American Air Defense Command (NORAD) when the computers flashed (for real, not as an exercise): "It is 99.9 percent certain that you are under attack!" In that neverbefore-faced situation, the decision had to be based on the "worse" of the two consequences: annihilate the Soviet Union, or be annihilated. In preparation for handling that one-of-a-kind situation, a less awesome, but extremely grave, decision situation that is repeatedly faced, is discussed: Hanging an innocent man. Central to both is the development of a Null Hypothesis (NH) based on the "worse" of the consequences: Hanging an innocent man, or letting a first-degree murderer go free.

Chapter 2 discusses one-of-a-kind and few-of-a-kind situations that use logical and subjective probabilities. Given that six out of six U.S. presidents elected to office in a year ending in zero died in office, what logical relationship can be . . .

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