What is convenience sampling in data science?

Convenience sampling is when people who are more easily accessible are included in the sample.

By performing convenience sampling, sources of bias can manifest in a variety of ways.

Convenience sampling is an example of non-random sampling.

Convenience sampling is also a type of non-probability sampling.

Advantages

• This method is significantly less time-consuming, as the individuals who are sampled are easier to select and analyze.
• This method looks at the ease of the person who is going to conduct the sampling. Therefore, it is an economical way of sampling.

Disadvantages

• The convenience sample fails to represent the entire population.
• When users need the information of the entire population and not just selective sampling, convenience sampling cannot be used.

Example

Suppose Tom wants to analyze the opinion of his school peers about whether the pandemic has affected their lives or not. Tom stands at his school’s entrance gate no. 1 and asks all the students entering from that gate to fill out the survey.

The scenario mentioned above is an example of convenience sampling, as Tom only surveys those who enter from gate no. 1. The opinions of sampled individuals are not at all representative of all of the school’s students.