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- W58906064 abstract "This chapter discusses the normal distribution. The normal distribution is a continuous, unimodal, and symmetric distribution that is loosely described as a bell-shaped curve. The standard deviation of sample means is called the standard error of the mean. The means of sufficiently large samples are normally distributed, or at least approximately so. A distribution of sampled statistics is called a sampling distribution. The chapter discusses the sampling distributions of means. In statistical inference, a pattern of chance events is identified in the form of some probability distribution. The tails of the normal distribution never actually touch the X axis. This implies that outcomes defined on even the most extreme intervals of the X axis are possible, though improbable. Many of the real-life events that are otherwise approximately normally distributed violate this assumption, that is, they do not have the possibility of infinitely large or small values. When the probabilities of outcomes are desired, a table that is derived from the equation for the normal distribution is used." @default.
- W58906064 created "2016-06-24" @default.
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- W58906064 date "1981-01-01" @default.
- W58906064 modified "2023-09-27" @default.
- W58906064 title "THE NORMAL DISTRIBUTION" @default.
- W58906064 doi "https://doi.org/10.1016/b978-0-12-445480-4.50012-1" @default.
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