Central limit theorem: the cornerstone of modern statistics
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Abstract
, distribute normally with mean, µ, and variance, [Formula: see text]. Using the central limit theorem, a variety of parametric tests have been developed under assumptions about the parameters that determine the population probability distribution. Compared to non-parametric tests, which do not require any assumptions about the population probability distribution, parametric tests produce more accurate and precise estimates with higher statistical powers. However, many medical researchers use parametric tests to present their data without knowledge of the contribution of the central limit theorem to the development of such tests. Thus, this review presents the basic concepts of the central limit theorem and…
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Keywords
- Central limit theorem
- Limit (mathematics)
- Parametric statistics
- Population
- Statistics
- Variance (accounting)
- Nonparametric statistics
- Sampling distribution
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