Question

What are ways to decrease sampling error?

Answer 1

Sampling error in statistics can be defined as the errors which arise due to unrepresentativeness of a sample from a population. It is one type of statistical error which occurs when an analyst does not select a sample that represents the population.

Sampling error is unavoidable, but they can be reduced. There are two ways to reduce sampling error:

1. By Increasing sample size: Sampling error and the sample size are negatively correlated. That means if sample size increases, sampling error decreases and vice versa. If the sample size = population size, then sampling error will be null(But this situation is not practical).This is because as sample size increases ,the sample gets closer to the population, and thereby decreases the potential for deviations from the actual population.
2. By stratification: For a population containing similar elements simple random sample is a good representative of the population. But for a population containing dissimilar elements, to improve the result of the sample, the design needs to be modified. The population is to be divided in different subgroups (strata) containing similar elements. From each strata (called stratum), a sub sample is selected at random. In this way all groups are represented in the sample and the sampling error is reduced.

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