Random Variables, Densities, and Cumulative Distribution Functions

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

Chapter 2 in Mathematical Statistics for Economics and Business, 1996, pp 43-107 from Springer

Abstract: Abstract The outcomes of many types of experiments are inherently in the form of real numbers. For example, measuring the height and weight of individuals, observing the market price and quantity demanded of a commodity, measuring the yield of a new type of wheat, or measuring the miles per gallon achievable by a new compact automobile all result in real-valued outcomes. The sample spaces associated with these types of experiments are subsets of the real line or, at least, subsets of n-dimensional real space, R n .

Keywords: Cumulative Distribution Function; Marginal Density; Continuous Random Variable; Joint Density Function; Conditional Density Function (search for similar items in EconPapers)
Date: 1996
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DOI: 10.1007/978-1-4612-3988-8_2

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