Explain Snowball sampling techniques.

Snowball sampling, also known as chain-referral sampling, is a non-probability sampling technique used in research where the target population is hard to reach or identify. This method is particularly useful in studies involving unique or sensitive characteristics, such as specific medical conditions, rare traits, or behaviors that are not openly discussed or are stigmatized.

The process begins with identifying a few individuals (known as 'seeds') who meet the study's criteria. These initial participants are then asked to refer others they know who also fit the criteria. The newly referred participants, in turn, refer more, creating a snowballing effect. As the process continues, the sample size grows, much like a snowball rolling down a hill.

One of the key advantages of snowball sampling is its ability to reach populations that are otherwise difficult to access through traditional sampling methods. It's particularly valuable in qualitative research where deep, contextual insights are more important than generalizability.

However, snowball sampling has limitations. The sample may not be representative of the entire population, leading to potential biases. The reliance on social networks means that the sample could be skewed towards certain characteristics or behaviors prevalent in those networks. Despite these limitations, snowball sampling remains a crucial tool in exploratory and qualitative research, especially in sensitive or niche areas where other sampling methods are impractical or ineffective.