In the field of Statistics, the sampling method, also known as the sampling methodology, refers to the systematic process of collecting and evaluating data in order to research a population. The data serves as the foundation, with a vast sample space.

There are several sampling strategies that may be categorized into two classes. All these sampling strategies may require particularly targeting hard-to-reach or difficult-to-approach groups.

### Sampling Methods

Statistics offers several sampling approaches to obtain meaningful data from a population. There are two distinct types of sampling methods:- Sampling method based on the principles of probability theory.
- Non-probability sampling refers to a method of selecting participants for a study that does not include random selection.

### 1. Probability Sampling Overview

- Probability sampling is a method that uses random selection to ensure a representative sample.
- It is more time-consuming and expensive than non-probability sampling but provides a reliable sample.

Types of Probability Sampling

**Simple Random Sampling:**Every item in the population has an equal chance of being selected in the sample.**Systematic Sampling:**Items are selected from the target population by selecting the random selection point and selecting other methods after a fixed sample interval.**Stratified Sampling**: The total population is divided into smaller groups based on certain characteristics.**Clustered Sampling:**Clusters or groups of people are formed from the population set with similar significatory characteristics. Example: Random sampling can be used to select three or four branches as clusters for data collection.

### 2. Non-Probability Sampling Methods Overview

a) Convenience or Haphazard Sampling:

- Assumes all population units are identical, allowing any unit to be selected for the sample.
- Example: vox pop survey where the interviewer selects any person who happens to walk by.
- Selection subject to the biases of the interviewer and whoever happened to walk by at the time of sampling.

- Respondents are volunteers, usually screened to get a set of characteristics suitable for the survey.
- Can be subject to large selection biases, but sometimes necessary.
- Example: callers to a radio or television show, where only those who care strongly enough about the subject tend to respond.
- Often used for focus groups or in-depth interviews.

C) Judgement Sampling:

- Sampling done based on previous ideas of population composition and behavior.
- An expert with knowledge of the population decides which units in the population should be sampled.
- Subject to the researcher’s biases and potentially more biased than haphazard sampling.
- Can be useful in exploratory studies, such as selecting members for focus groups or in-depth interviews.

D) Quota Sampling:

- One of the most common forms of non-probability sampling.
- Sampling done until a specific number of units (quotas) for various sub populations have been selected.
- Quota sampling is preferable to other forms of non-probability sampling because it forces the inclusion of members of different sub populations.
- Unlike stratified sampling, quota sampling uses a non-random method, leaving the interviewer to decide who is sampled.

E) Snowball and Crowdsourcing in Research

- Snowball sampling is a method used to find rare or hard-to-reach populations, such as people with disabilities, homeless people, drug users, or non-organized groups.
- However, some individuals or subgroups may not be included in the sample.

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