In a sample survey, since only a small portion of the population is studied its results are bound to differ from the census results and thus, have a certain amount of error. In statistics, the word ‘error’ is used to denote the difference between the true value and the estimated or approximated value. This error would always be there, no matter that the sample is drawn at random and that it is highly representative. This error is attributed to fluctuations of sampling and is called sampling error. Sampling error exists because only a subset of the population has been used to estimate the population parameters and draw inferences about the population. Thus, the sampling error is present only in a sample survey and is completely absent in the census method. These sampling errors occur primarily due to the following reasons:
Faulty selection of the sample
Some of the bias is introduced by the use of defective sampling technique for the selection of a sample e.g. Purposive or judgment sampling in which the investigator deliberately selects a representative sample to obtain certain results. This bias can be easily overcome by adopting the technique of simple random sampling.
When difficulties arise in enumerating a particular sampling unit included in the random sample, the investigators usually substitute a
convenient member of the population. This obviously leads to some bias since the characteristics possessed by the substituted unit will usually be different from those possessed by the unit originally included in the sample.
Faulty demarcation of sampling units
Bias due to the defective demarcation of sampling units is particularly significant in area surveys such as agricultural experiments in the field of crop cutting surveys etc. In such surveys, while dealing with borderline cases, it depends more or less on the discretion of the investigator whether to include them in the sample or not.
Error due to bias in the estimation method
Sampling method consists of estimating the parameters of the population by appropriate statistics computed from the sample. Improper choice of the estimation techniques might introduce the error.
Variability of the population
Sampling error also depends on the variability or heterogeneity of the population to be sampled.
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