Central Limit Theorem Definition and Explanation PDF | Download eBooks
Learn Central Limit Theorem definition in total quality management with explanation to study “What is Central Limit Theorem”. Study central limit theorem explanation with TQM terms to review total quality management course for online MBA programs.
Central Limit Theorem Definition:
Central limit theorem implies that the sum of independently distributed random variables is approximately normal, regardless of the distributions of the individual variables.
Introduction to Statistical Quality Control by Douglas C. Montgomery
Central Limit Theorem Explanation:
An important concept in statistics and probability is central limit theorem. Central limit theorem is linked with sample means. This theorem states that even if the data values are non-normal, the distribution of sample means will be approximately normal. The central limit theorem is valid for large sample sizes. It shows that for large sample sizes the sample probability distribution tend to become normal regardless of the probability distribution of the population. As large sample size is the key in this theorem, the size of the sample depends on two factors; requirement for accuracy, and shape of the population distribution.
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