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Sampling Error
It is the difference between the value of the actual population parameter and the sample statistic.
Samples are used to arrive at conclusions regarding the population. For example, the sample mean is computed to arrive at an estimate of the population mean. However, the sample mean may not be equal to the population mean. The difference between the two means would be the Sampling Error.
Box 1: Error Terror
Hi Financials Ltd. recently commissioned a market survey to assess the growth in the number of equity investors in the country. A preliminary report revealed a sharp decline in the number of equity investors and raised several eyebrows in the board room. However, it was later clarified that the preliminary report was based on very small sample so that the conclusion was not applicable to the population as a whole. It was a case of sampling error.
A subsequent survey involving a larger sample revealed a healthy growth in the equity investor population.
If the test is two-tailed, H1: μ ≠ μ 0 then the test is called two-tailed test and in such a case the critical region lies in both the right and left tails of the sampling distr
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