When testing the safety of cars using crash tests, a sample of one or two cars is used because cars are destroyed.
While using stratified random sampling, the sampling error could be 0. In all forms of sampling, sampling errors, the difference between the population fee and the pattern statistic, will arise. We will anticipate some variations between sample facts and the corresponding population parameters.
If the sample length n is equal to the population length N, then the sampling error is zero. Stratification: while the population carries homogeneous units, an easy random pattern is likely to be representative of the population.
The prevalence of sampling errors may be reduced by means of growing the sample length. As the pattern size will increase, the sample gets in the direction of the real populace, which decreases the capability for deviations from the real population.
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