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(1) A sample may save money (as compared with the cost of a complete census) when absolute precision is not necessary.

(2) A sample saves time, when data are desired more quickly than would be possible with a complete census.

(3) A sample may make it possible to concentrate attention on individual cases.

(4) In industrial uses, some tests are destructive (for example, testing the length of time an electric bulb will last) and can only be performed on a sample of items.

(5) Some populations can be considered as infinite, and can, therefore, only be sampled. A simple example is an agricultural experiment for testing fertilizers. In one sense, a census can be considered as a sample at one instant of time of an underlying causal system which has random features in it.

(6) Where non-sampling errors are necessarily large, a sample may give better results than a complete census because non-sampling errors are easier to control in smaller-scale operations

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