a. Simple random sampling :-
– Applicable when population is small, homogeneous & readily available.
– Each element of the frame thus has an equal probability of selection.
– Sampling schemes may be without replacement or with replacement.
Advantages:
• Estimates are easy to calculate.
• Freedom from the human bias
Disadvantages:
• If sampling frame large, this method impracticable.
• Minority subgroups of interest in population may not be present in sample in sufficient numbers for study.
b. Systemic sampling:-
– Arranging the target population according to some ordering scheme (i.e. 1 to N)
– Decide on the n ( sample size) that you want or need
– Interval size will be K = N/n
– Randomly select an integer between 1-K
– Then take every k th unit as a sample
Advantages:
• Sample easy to select
• Suitable sampling frame can be identified easily
• Sample evenly spread over entire reference population
Disadvantages:
• Sample may be biased if hidden periodicity in population coincides with that of selection.
• Difficult to assess precision of estimate from one survey.
c. Stratified sampling:-
– If population is heterogeneous then this method is used.
– The items should be selected on the basis of simple random sampling from each stratum.
Advantages
• Adequate representation of minority subgroups of interest can be ensured by stratification
• Different sampling approaches can be applied to different strata.
Disadvantages
• Sampling frame of entire population has to be prepared separately for each stratum.
• In some cases (such as designs with a large number of strata, or those with a specified minimum sample size per group), stratified sampling can potentially require a larger sample than would other methods.
d) Cluster Sampling:-
– This method is useful if area of interest is big.
Advantages
• Reduces cost by concentrating surveys in selected clusters.
Disadvantages
• Less precise than random sampling
• There is also not as much information in ‘n’ observations within a cluster as there happens to be in ‘n’ randomly drawn observations.
e) Multistage sampling:-
– More complicated form of cluster sampling in which larger clusters are further subdivided into smaller, more targeted groupings for the purposes of surveying.