Probability and non probability sampling techniques Probabili | Morning Star Research, Training and Consultancy

Probability and non probability sampling techniques
Probability sampling techniques involve selecting a sample from a population using a method that gives each member of the population an equal chance of being selected. Some common probability sampling techniques include:

Simple random sampling: This involves selecting a sample at random from the population, where each member of the population has an equal chance of being selected.

Systematic sampling: This involves selecting a sample by choosing every nth member of the population, where n is a fixed interval calculated by dividing the population size by the desired sample size.

Stratified sampling: This involves dividing the population into subgroups based on certain characteristics, and then selecting a sample from each subgroup in proportion to its size in the population.

Cluster sampling: This involves dividing the population into clusters or groups, and then selecting a random sample of clusters to be included in the study. All individuals within the selected clusters are then included in the sample.

On the other hand, non-probability sampling techniques do not involve random selection of participants. Instead, the selection of participants is based on other factors, such as availability, willingness to participate, or the researcher's judgment. Some common non-probability sampling techniques include:

Convenience sampling: This involves selecting participants who are easily accessible or available at the time of the study.

Quota sampling: This involves selecting participants to ensure that the sample has the same proportions of certain characteristics as the population.

Purposive sampling: This involves selecting participants based on specific criteria, such as their expertise or experience relevant to the research question.

Snowball sampling: This involves selecting participants through referrals from other participants in the study.