Each statistical estimate derived from a sample of the population will differ by some amount from other samples. This difference between samples is the sampling error.
(Garth Frazer, PPG1004, MPP 2008)
Any estimates derived from samples are subject to what is called the sampling error. This comes from the fact that only a part of the population was observed, instead of the whole. A different sample could have come up with different results. The amount of variation that exists among the estimates from the different samples is the sampling error. Of course, this sampling error is unknown, since we would need to know the answer for each unit of the population in order to calculate it. Nevertheless, it can be estimated by using survey data. The extent of the sampling error depends on many things, including the sampling method, the estimation method, the sample size and the variability of the estimated characteristic.