Probability Sampling Methods

Probability Sampling Methods

• The method of sampling, not the size of the sample or population, determines whether it's probability or non-probability sampling.

Simple Random Sampling

• All members of the population have an equal probability of being selected for the sample, expressed by the formula: Probability of selection = Sample Size / Population Size.
• Examples include the "blind draw" method and the table of random numbers method.
• Blind draw method: blindly choosing participants by their names or unique designations.
• Table of random numbers method: using a table of random numbers to ensure randomness.

Systematic Sampling

• A probability sampling technique that is often more efficient than simple random sampling.
• Involves a random starting point and a skip interval calculated by dividing the population size by the sample size.
• Example: if the population size is 100,000 and the sample size is 1,000, the skip interval is 100.

Cluster Sampling

• Used for large populations, scattered distributions, or when individual selection is not convenient.
• Involves selecting clusters or groups of the population, such as schools or regions, rather than individual members.
• Example: selecting a sample of 4th-grade students in elementary schools in Ethiopia by random sampling of schools and teachers.

Non-Probability Sampling

• Does not involve probability calculations for selecting samples.
• Examples include convenience sampling, quota sampling, snowball sampling, and judgment sampling.

Convenience Sampling

• A non-probability sampling method that involves selecting samples based on convenience, such as location or accessibility.
• Selection is subjective, and certain members of the population may be excluded, such as those who do not frequent high-traffic areas.