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rabbit · 2021年02月18日

切比不等式

NO.PZ2017092702000157

问题如下:

For a distribution of 2,000 observations with finite variance, sample mean of 10.0%, and standard deviation of 4.0%, what is the minimum number of observations that will lie within 8.0% around the mean according to Chebyshev's Inequality?

选项:

A.

720

B.

1500

C.

1680

解释:

B is correct. Observations within 8% of the sample mean will cover an interval of 8/4 or two standard deviations. Chebyshev’s Inequality says the proportion of the observations P within k standard deviations of the arithmetic mean is at least 1 - 1/k2 for all k > 1. So, solving for k = 2: P = 1 – ¼ = 75%. Given 2,000 observations, this implies at least 1,500 will lie within 8.0% of the mean.
A is incorrect because 720 shows P = 720/2,000 = 36.0% of the observations. Using P to solve for
k implies 36.0% = 1 – 1/k
2, where k
= 1.25. This result would cover an interval only 4% × 1.25 or 5% around the mean (i.e. less than two standard deviations).
C is incorrect because 1,680 shows P = 1,680/2,000 = 84.0% of the observations. Using P to solve for
k implies 84.0% = 1 – 1/k
2, where k
= 2.50. This result would cover an interval of 4% × 2.5, or 10% around the mean (i.e., more than two standard deviations).

老师,您好,这道题提到了的均值和方差是样本值,为什么不是K倍的 S/(根号下N),即标准误?切比雪夫不等式是只针对总体的均值和方差吗?

1 个答案

星星_品职助教 · 2021年02月19日

同学你好,

要区分一下“样本的分布”和“样本均值的分布”

以本题为例,一个样本包含2000个观察值,这2000个数据的分布就是样本自身的分布,这个“样本”的分布的均值是10.0%,这个“样本”的分布的标准差是4.0%。

而标准误是“样本均值”的标准差。具体而言,根据中心极限定理,如果对于'样本均值专门画出一个分布,那么这个分布(即样本均值的分布)的均值就是总体均值μ,这个“样本均值的分布”的标准差就是标准误,标准误=总体标准差/根号n 

所以回到本题,切比雪夫不等式关注的是抽出来的那个样本本身的分布(及其样本均值和样本标准差),此时并不需要考虑样本均值的分布是什么样子的,也就不需要计算标准误了。

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但其实最简单的理解角度是切比雪夫不等式和标准误分属两个不同的考点,是不会混在一起考的。

切比雪夫不等式的常规考法是直接给出分布的均值和标准差,然后套用公式即可。

 

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