Sampling error refers to the differences between the sample estimate and the actual value of a characteristic of the population. It is the error that occurs when you make an observation from the samples taken from the population.
Thus, the difference between the actual value of a parameter of the population and its estimate is the sampling error. It is possible to reduce the magnitude of sampling error by taking a larger sample.
For example, suppose the height of 5 students (in inches) are 50, 55, 60, 65, 70. Now, the average height will be calculated by adding all these observations and dividing the sum by 5 . then we get 60 inches. If we select a sample of two students with height of 50 and 60 inches, then average height of sample will be 50 + 60 divided by 2, we get 55 inches. Here the sampling error of the estimate will be 60 (true value) minus 55 (estimate) = 5.