Sequential Sampling


In sequential sampling, a number of samples n1, n2, n3…nx are randomly drawn from the population It is not at all necessary that each sample should be of the same size Generally, the first sample is the largest, the second is smaller than the first, the third is smaller than the second, and so on


A sequential sampling is resorted mainly to bring down the cost and hence the smallest possible sample is used The desired statistics from first sample, ni, are computed and evaluated If these statistics do not satisfy the criteria laid down, a second sample is drawn The results of the first and second samples are added and the statistics are recomputed This process is continued until the specified criteria are satisfied The criteria are usually a minimum significance level, a minimum cluster size, or a minimum confidence interval


The main advantage of sequential sampling is that it obviates the need for determining a fixed sample size before the commencement of the survey


Suppose a firm is to decide whether a new product is to be introduced in the market or not It feels that if it is able to acquire 15 per cent market share in a country within a year, it should introduce the new product Further, it feels that if a market share of 10 per cent in a few test markets is achieved, it would be possible to acquire a 15 per cent market share in the country, say, within a period of six months Now, when the firm has undertaken test marketing, it actually achieved far more than 10 per cent, say, 20 per cent, of the market share and that too within three months of test marketing The firm may be sure to achieve the 15 per cent national market share within one year even though it may not be possible for it to accurately forecast the test market share at the end of four months

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