Sampling Distributions

  • T. W. Anderson
  • Jeremy D. Finn


Statistical inference is the process of drawing conclusions about a population of interest from a sample of data. In order to develop and evaluate methods for using sample information to obtain knowledge of the population, it is necessary to know how closely a descriptive quantity such as the mean or the median of a sample resembles the corresponding population quantity. In this chapter the ideas of probability will be used to study the sample-to-sample variability of these descriptive quantities. The ways in which one sample differs from another, and thus how they are both likely to differ from the corresponding population value, is the key theoretical concept underlying statistical inference.


Central Limit Theorem Sampling Distribution Independent Random Variable Normal Curve Parent Population 
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Copyright information

© Springer-Verlag New York, Inc. 1996

Authors and Affiliations

  • T. W. Anderson
    • 1
  • Jeremy D. Finn
    • 2
  1. 1.Department of StatisticsStanford UniversityStanfordUSA
  2. 2.Graduate School of EducationState University of New York at BuffaloBuffaloUSA

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