Central Limit Theorem

  • Allan J. Rossman
  • Beth L. Chance
Part of the The Workshop Mathematics Project book series (TIMS)

Overview

In previous activities you have sampled candies, rolled dice, and performed Minitab simulations to discover that while the value of a sample statistic varies from sample to sample, there is a very precise long-term pattern to that variation. In the last activity you learned how to use normal distributions to perform probability calculations. This topic brings those two ideas together through the Central Limit Theorem. This result asserts that the long-term pattern of the variation of a sample proportion is that of a normal distribution. You will examine implications and applications of this theorem in detail, focusing on how it lays the foundation for widely used techniques of statistical inference.

Keywords

Central Limit Theorem Sampling Distribution Simple Random Sample Presidential Election Population Proportion 
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 1998

Authors and Affiliations

  • Allan J. Rossman
    • 1
  • Beth L. Chance
    • 2
  1. 1.Dickinson CollegeUSA
  2. 2.University of the PacificUSA

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