Which type of sampling does not follow a random process for selection?

Non-random sampling is characterized by a selection process that does not rely on randomization, which means that not every individual or element in a population has a known, non-zero chance of being selected. This approach can involve various methods where researchers intentionally select specific individuals based on certain criteria, making it non-representative of the entire population.

This type of sampling is useful in exploratory research, qualitative studies, or when specific expertise is required from certain individuals. For instance, if a researcher wants to gather insights from experts in a field, they may use non-random sampling to target specific individuals who have the necessary knowledge or experience. This is in contrast to probability sampling methods, which are designed to ensure that every member of the population has a chance to be included in the sample, thereby allowing for more generalizable and statistically valid results.

By choosing non-random sampling, researchers can focus on particular segments of a population or specific attributes they want to investigate, making it a strategic choice in certain scenarios.