Sampling is the most important process in statistics. All the statistical estimation and results are based upon the sampling of the data. Sampling is the process of collection of information and its analysis. Statistical sampling is quite useful in various fields when the population size is very big and is not easier to manage and study.

For statistical sampling, there are different methods that are used by researchers in order to collect and analyze data. Few of the popular techniques or methods are given below:

- Random Sampling
- Systematic Sampling
- Cluster Sampling
- Stratified Sampling
- Convenience Sampling

**Random Sampling**

While dealing with very large data, it is almost impossible to recognize each data. There are very fair chances of bias in this case. Random sampling is a type of sampling in which every member has same probability of being considered. It means that each population is not further divided. **For example:** Choosing a card randomly from a deck of 52 cards is a good example of random sampling. Here, chances of choosing each card is same.

**Systematic Sampling**

In systematic sampling, the population is divided into small and equal intervals. Systematic sampling starts randomly. After that, every $n^{th}$ member is selected, where n is the sample size. In this type of sampling, the point of start is chosen randomly, it is not necessarily the first element. **For example:** If we have to choose 100 telephone numbers from directory, then every $50^{th}4 number can be selected after choosing a random number.

**Cluster Sampling**

According to this method, the population is partitioned into clusters or groups. In case of very big population size, instead of choosing an individual item, it is much more easier and cost effective to choose the clusters. Analysis can be done by taking random sample from one or more clusters.

Stratified method of sampling is used when the population has different categories or strata (plural - stratum). A stratum can be then randomly selected, from which the elements can be analyzed easily.

**Convenience Sampling**** **

In this method, the researcher chooses elements as per his/her convenience and availability of the samples. This may lead to an unreliable result at times.

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More topics in Sampling Methods | |

Simple Random Sample | Systematic Sampling |

Stratified Sampling | Cluster Sampling |