The Law of Large Numbers and the Central Limit Theorem

  • Richard L. Scheaffer
  • Ann Watkins
  • Mrudulla Gnanadesikan
  • Jeffrey A. Witmer
Part of the Textbooks in mathematical sciences book series (TIMS)

Abstract

When pollsters ask a question such as “Do you approve of the job performance of the president?” they usually take large samples. They expect the sample percentage to be close to the population percentage, but they are never certain if their results are accurate. likewise, suppose you toss a coin over and over again and keep track of the percentage of heads obtained along the way. You expect to get heads half of the time, but that doesn’t mean that you’ll get exactly 50 heads in the first 100 tosses. As the number of tosses goes up, you expect the sample percentage to approach 50%, but there will be variability.

Keywords

Scatter Plot Central Limit Theorem Sample Path Selector Variable Color Palette 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 1996

Authors and Affiliations

  • Richard L. Scheaffer
    • 1
  • Ann Watkins
    • 2
  • Mrudulla Gnanadesikan
    • 3
  • Jeffrey A. Witmer
    • 4
  1. 1.University of FloridaUSA
  2. 2.California State UniversityNorthridgeUSA
  3. 3.Fairleigh Dickinson UniversityUSA
  4. 4.Oberlin CollegeUSA

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