Central Limit Theorem

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Many statistical inferential procedures such as hypothesis testing and the estimation of confidence intervals are based on the assumption that the distribution of a sample statistic is normal. The Central Limit Theorem (CLT) often justifies the assumption that the distribution of a sample statistic (e.g., mean, sum score, and test statistic) is normal. The Central Limit Theorem states that, for a large sample of n observations from a population with a finite mean and variance, the sampling distribution of the sum or mean of samples of size n is approximately normal.
Original languageEnglish (US)
Title of host publicationThe Corsini Encyclopedia of Psychology
EditorsIrving B. Weiner, W. Edward Craighead
PublisherJohn Wiley & Sons, Inc.
ISBN (Electronic)9780470479216
DOIs
StatePublished - Jan 30 2010

Keywords

  • mean
  • sum
  • population
  • sampling distribution
  • normal distribution

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