Elements of Probability Theory

Ron C. Mittelhammer
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Ron C. Mittelhammer: Washington State University, Program in Statistics and Department of Agricultural Economics

Chapter 1 in Mathematical Statistics for Economics and Business, 1996, pp 1-42 from Springer

Abstract: Abstract The objective of this chapter is to define a quantitative measure of either the level of certainty (or uncertainty) associated with observing various outcomes of a chance situation, or the degree of belief in a stated proposition. The quantitative measure, called probability, is relevant for quantifying such things as how likely it is that a shipment of transistors contains less than 5 percent defectives, that a gambler will win a crap game, that next year’s corn yields will exceed 80 bushels per acre, or that electricity demand in Los Angeles will exceed generating capacity on a given day. The probability concept will also be relevant for quantifying an individual’s degree of belief in such propositions as it will rain tomorrow, Congress will raise taxes next year, and the United States will suffer another oil embargo in the coming year.

Keywords: Conditional Probability; Assembly Line; Mutual Fund; Sample Space; Subjective Probability (search for similar items in EconPapers)
Date: 1996
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DOI: 10.1007/978-1-4612-3988-8_1

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