NO.PZ2017092702000105
问题如下：
Suppose we take a random sample of 30 companies in an industry with 200 companies. We calculate the sample mean of the ratio of cash flow to total debt for the prior year. We find that this ratio is 23 percent. Subsequently, we learn that the population cash flow to total debt ratio (taking account of all 200 companies) is 26 percent. What is the explanation for the discrepancy between the sample mean of 23 percent and the population mean of 26 percent?
选项：
A.Sampling error.
B.Bias.
C.A lack of consistency
解释：
A is correct.
The discrepancy arises from sampling error. Sampling error exists whenever one fails to observe every element of the population, because a sample statistic can vary from sample to sample. As stated in the reading, the sample mean is an unbiased estimator, a consistent estimator, and an efficient estimator of the population mean. Although the sample mean is an unbiased estimator of the population mean—the expected value of the sample mean equals the population mean—because of sampling error, we do not expect the sample mean to exactly equal the population mean in any one sample we may take.
差异源于抽样误差。 每当未能观察到总体的每个元素时，就会存在抽样误差，因为样本统计量可能因样本而异。 如文中所说，样本均值是总体均值的无偏估计量、一致估计量和有效估计量。 尽管样本均值是总体均值的无偏估计量（样本均值的期望值等于总体均值），但由于抽样误差，我们并不期望样本均值与我们可能采用的任何样本中的总体均值完全相等 .
如题。。。。。。。。。
