### Types of sampling techniques

Generally there are two types of sampling techniques which are described below:
1. Probability (Random) sampling technique
2. Non-probability (non-random) sampling technique
1. Probability (Random) sampling
A type of sampling technique in which every unit of the population has an equal chance of being selected in the sample is known as probability sampling. In this method, selection of the sample is based on the theory of probability. This type of sampling is also referred as random sampling. Here, the term random does not means the haphazard or without any purpose. It is a systematic process.

Probability sampling is further sub-divided in the following types:
a) Simple random sampling
b) Stratified sampling
c) Systematic sampling
d) Cluster sampling
e) Multi-stage sampling

1. Simple random sampling: The simplest and most common method of sampling is simple random sampling. In this method, each and every unit of the population has equal chance of being included in the sample. It is also sometimes referred as unrestricted random sampling.

If a unit is selected and noted and then returned to the population before the next drawing is made and this procedure repeated many times, gives to required to many sample. This procedure is generally known as simple random sampling with replacement (SRSWR). If the selected unit is not returned to the population before the next drawing is made, this is known as simple random sampling  without replacement (SRSWOR).

2. Stratified sampling: Stratified sampling is a type of restricted random sampling. In this technique, first the whole population is divided into homogeneous groups under certain criterion. These groups are called strata. Then the sample is drawn from each stratum. Proper care should be taken while making strata.

In stratified sampling, the allocation of the sample to different strata is done by the consideration of three factors: stratum size, the variability within the stratum and the cost in taking observations per sample in the stratum. A good allocation is one where maximum precision is obtained with minimum resources. Mainly there are four methods of allocation of samples sizes to different strata in a stratified sampling. There are equal allocation, propotional allocation, Neyman allocation and optimum allocation.

3. Systematic sampling: A sampling technique in which only the first unit is selected with the help of random numbers and the rest get selected automatically according to some pre-designed pattern is known as systematic sampling.

4. Cluster sampling: The entire population is divided into the smallest unit. A group of such unit is known as a cluster. When the sampling unit is cluster, the procedure is called cluster sampling. Generally the cluster sampling is used when the sampling frame for elementary units of the population is not available.

5. Multi-stage sampling: A type of sampling which consists in first selecting the clusters and then selecting a specified number of elements from each selected cluster is known as two-stage sampling. The selection procedure can extended to any number of stages. Hence, in general, it is known as multi-stage sampling. This type of sampling has been commonly used in large-scale surveys.