Sample Size and Statistical theory - Sequential Sampling
Sequential Sampling
Sometimes a researcher may want to take a modest sample, look at the results, and then decide if more information, in the form of a larger sample, is needed. Such a procedure is termed sequential sampling. If a new industrial product were being evaluated, a small probability sample of potential users might be contacted. Suppose it were found that their average annual usage level at a 95 percent confidence level was between 10 and 30 units, and it was known that for the product to be economically viable the average would have to be 50 units. This is sufficient information for a decision to drop the product. If, however, the interval estimate from the original sample were from 45 to 65, then the information would be inadequate for making that decision and an additional sample might be obtained. The combined samples then would provide a smaller interval estimate. If the resulting interval were still inadequate, the sample size could be increased a third time. Of course, although sequential sampling does provide the potential of sharply reducing costs, it can result in increased costs and a delayed decision.
The concept of sequential sampling is useful because it reminds the researcher that the goal of marketing research is to provide information to aid in decision making. The quality of the information must be evaluated in the decision-making context. Too often, information tends to be evaluated absolutely (it is intellectually comfortable to be "certain"). Instead, it should be judged with respect to its use.
Sometimes a researcher may want to take a modest sample, look at the results, and then decide if more information, in the form of a larger sample, is needed. Such a procedure is termed sequential sampling. If a new industrial product were being evaluated, a small probability sample of potential users might be contacted. Suppose it were found that their average annual usage level at a 95 percent confidence level was between 10 and 30 units, and it was known that for the product to be economically viable the average would have to be 50 units. This is sufficient information for a decision to drop the product. If, however, the interval estimate from the original sample were from 45 to 65, then the information would be inadequate for making that decision and an additional sample might be obtained. The combined samples then would provide a smaller interval estimate. If the resulting interval were still inadequate, the sample size could be increased a third time. Of course, although sequential sampling does provide the potential of sharply reducing costs, it can result in increased costs and a delayed decision.
The concept of sequential sampling is useful because it reminds the researcher that the goal of marketing research is to provide information to aid in decision making. The quality of the information must be evaluated in the decision-making context. Too often, information tends to be evaluated absolutely (it is intellectually comfortable to be "certain"). Instead, it should be judged with respect to its use.
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