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z scores are the standardized values obtained after converting a normal distribution into a standard normal distribution. A z score is measured in units of the standard deviation. The z score tells you how many standard deviations the value x is above (to the right of) or below (to the left of) the mean, μ. Values of x that are larger than the mean have positive z scores, and values of x that are smaller than the mean have negative z scores. If x equals the mean, then x has a z score of zero. The z score allows us to compare data that are normally distributed but scaled differently.

A standardized graph can help determine the probability function. The area under the density curve between two points corresponds to the probability that the variable falls between those two values. The area under the curve is always 1. One can also find the area for a particular z score by referring to the z score table, which shows the cumulative areas under the standard normal distribution from the left side of the curve.

This text is adapted from Openstax, Introductory Statistics, Section 6.1

Tags
Z ScoresStandard Normal DistributionMeanStandard DeviationProbability FunctionDensity CurveArea Under The CurveCumulative AreasZ Score TableNormal Distribution

来自章节 6:

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6.11 : z Scores and Area Under the Curve

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6.1 : 统计中的概率

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6.2 : 随机变量

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6.3 : 概率分布

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6.4 : 概率直方图

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6.5 : 不寻常的结果

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6.6 : 期望值

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6.7 : 二项式概率分布

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6.8 : 泊松概率分布

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6.9 : 均匀分布

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6.10 : 正态分布

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6.12 : 正态分布的应用

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6.13 : 抽样分布

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6.14 : 中心极限定理

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