Q: Explain the different types of non- probability sampling techniques. Bring out the conditions of their usage with appropriate examples.

Model Answer:

Types of Non-Probability Sampling

Non-probability sampling techniques are methods of selecting participants for a study where each individual in the population does not have an equal chance of being selected. These techniques are often used when it is difficult or impractical to obtain a random sample. Here are the different types of non-probability sampling techniques and the conditions for their usage with examples:

1. Convenience Sampling:

In this method, participants are selected based on their availability and ease of access. It is often used when time and resources are limited, and the researcher needs to quickly gather data.

Example: A researcher wants to study the opinions of people about a new product. They decide to survey people at a nearby shopping mall, as it is convenient and provides a diverse group of potential participants.

2. Judgmental or Purposive Sampling:

This technique involves selecting participants based on specific criteria or characteristics that are relevant to the study. The researcher uses their judgment to identify individuals who are most likely to provide valuable information.

Example: A researcher wants to study the experiences of women entrepreneurs in a particular industry. They would select participants who are women entrepreneurs in that industry, as they are most likely to provide relevant information.

3. Quota Sampling:

In quota sampling, the researcher selects participants based on specific characteristics, aiming to represent the population proportionally. The researcher sets quotas for each category, and once the quota is filled, no more participants from that category are selected.

Example: A researcher wants to study the political opinions of people in a city. They decide to select participants based on age, gender, and ethnicity to ensure that the sample represents the city’s population.

4. Snowball Sampling:

This technique is used when the target population is hard to reach or identify. The researcher begins by selecting a few participants who meet the criteria and then asks them to refer others who also meet the criteria. The process continues until the desired sample size is reached.

Example: A researcher wants to study the experiences of undocumented immigrants. They would start by interviewing a few undocumented immigrants and ask them to refer others in their community, as this population is hard to reach through traditional sampling methods.

5. Self-selection Sampling:

In this method, participants voluntarily choose to be part of the study, often in response to an advertisement or invitation. This technique can be useful when studying sensitive topics, as participants are more likely to provide honest information if they choose to participate.

Example: A researcher wants to study the impact of a new mental health intervention. They advertise the study in local newspapers and online forums, inviting individuals who have experienced mental health issues to participate.

Each of these non-probability sampling techniques has its advantages and limitations, and the choice of method depends on the research question, population, and available resources. While non-probability sampling techniques may not provide results that are as generalizable as probability sampling methods, they can still offer valuable insights and contribute to our understanding of various phenomena.