Systematic Random Sampling in Research
In cluster sampling the population again is subdivided into subgroups termed clusters instead of strata. The term cluster means a bunch of similar things. Suppose the thousand employees of a factory in our example comprise of teams each consisting of one supervisor and nine workers, and we choose these teams at random, it is a cluster sample, because we have taken one hundred clusters as our sample. One popular type of cluster sample is the systematic random sample also called quasi-random sample. Suppose the thousand employees of the factory are listed alphabetically and numbered serially to form the sample frame. (The alphabetical order is usually a random arrangement with respect to most characteristics and so forms an unbiased sample frame). As twenty employees are to be chosen from the thousand, it is a one in fifty sample. So, here, 50 is the sampling interval or ‘skip factor’. Now choose a Continue reading