Sampling and Sampling Distributions

Cheng-Few Lee, John C. Lee and Alice C. Lee
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Cheng-Few Lee: Rutgers University Business School, Department of Finance and Economics
John C. Lee: Center for PBBEF Research

Chapter Chapter 8 in Statistics for Business and Financial Economics, 2013, pp 331-379 from Springer

Abstract: Abstract In this chapter, we take an in-depth look at the operational end of statistical analysis. Statistical analysis primarily involves selecting parts of populations (known as samples) and analyzing them in order to make inferences about the populations. Inferences made about a population by using sample data are widespread in business, economics, and finance. For example, the A. C. Nielsen Company infers the number of people who watch each television show on the basis of a sample of TV viewers. The use of political polls to project election winners is another example of statistical inference. And when you fill out a warranty card on an appliance you have bought, you are often asked to provide information about yourself that the warrantor compiles (and probably sells to someone who will later try to convince you to buy a magazine subscription). These data are also sample data.

Keywords: Sampling Error; Central Limit Theorem; Sampling Distribution; Mutual Fund; Simple Random Sample (search for similar items in EconPapers)
Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-1-4614-5897-5_8

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DOI: 10.1007/978-1-4614-5897-5_8

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