Sampling Error is the difference between the results obtained from a sample and the results obtained from the population from which the sample was selected.

For example, suppose you select a sample of full-time students at your college and find 56% are female. Then you go to the admissions office and get the genders of all full-time students that semester and find that 54% are female. The difference of 2% is said to be due to sampling error.

Non-Sampling Error occurs when the data is obtained erroneously or the sample is biased, i.e., nonrepresentative.