There are two types of error that we may find occurring when the effort is to try and estimate the parameters of the population from the sample. These errors can be classified as sampling and non-sampling errors.
Sampling error: This kind of error is often seen arising when the sample of the study does not represent the population that has to be studied. To understand better with an example, if the entire population comprises 200 MBA students of a business school and the research focus is to estimate the average height of these 200 students. The sample chosen is, let’s say, 10 students. In this case if we assume that the true mean of the population is known and the analysis show us that there is a wide difference between the sample mean and population mean. This kind of an error falls in the category of a sampling error. The reason for this kind of an error is the chosen sample size. In the above case, a sample of 10 is not a representative of the entire population. If the sample size is increased to 15 the error reduces. A significant increase in the sample size on one side significantly reduces the error on the other side.
Non Sampling error: This error arises because of various reasons. Some of the reasons are:
a) False or incorrect information given by the respondents may lead to a non-sampling error. For example, sometimes the respondent may not disclose his correct age and this may bring up a non-sampling kind of error.
b) Sometimes error arises when the transfer of data is being done onto a spreadsheet, from a manual sheet which is the questionnaire.
c) There are some errors that may happen at the time of coding or tabulation.
d) At times, it so happens, that the population of the study is not defined in the correct manner. It leads to errors.
e) The respondent that the researcher chooses for study, at times refuses to become a part of the study. This also becomes a kind of non-sampling error.
f) Another type of non-sampling error is the error of the sampling frame. Sometimes, the researcher decides to ignore a certain category of respondents and that may lead to the development of a non-sampling error.