In statistics, a simple random sample from a population is a sample chosen randomly, in which each member of the population has the same probability of being chosen. In small populations such sampling is typically done "without replacement", i.e., one deliberately avoids choosing any member of the population more than once.
Conceptually, simple random sampling is the simplist of the probability sampling techniques, but it is seldom used in practice because of application problems. Simple random sampling is not an efficient method. It requires constructing a very large sampling frame and this results in extensive sampling calculations and excessive costs. If researchers were to consider the information available about the population, a more efficient approach could be used.
Advantages are that it is free of classification error, and it requires minimum advance knowlegde of the population. It best suits situations where the population is fairly homogeneous and not much information is available about the population. If these conditions are not true, stratified sampling may be a better choice.