Correlation Between Sampling, Sampling Risk And Nonsampling Risk

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Sampling means take one typical part of from the whole population, which is an essential method for corporations to get the result of their new products or policies. When corporations test the sample, they do not actually need the specific data and number. In addition, the total number of comprising the population is usually large, so the corporations usually do not test the whole population for reducing meaningless time and labor cost. Sampling is a good way to trade effectiveness to efficiency. Thus, the results of sampling are always directly connected with and also affected the applying or changing of products and polices of corporations.

There are two kinds of risk of sample, sampling risk and nonsampling risk, during the process of sampling. Sample always causes risk because the sample does not include all of the information of the whole population in the test. Thus, it is entirely possible that the sample does not show the correct result of examination to the test engagement team. For example, in the case of Wilson Corporation, the engagement team of Wilson tested 50 golfers as sample for calculating the distances for the new golf to make sure whether that Wilson’s golf balls provided an increase of distance. The engagement team is interested in determining whether the increase in distance is more than five yards. We assume that true average increase in distance is seven yards if the engagement tests all of the golf players’ data. So the team can get the correct
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