What are the differences between sampling methods?

What are the differences between sampling methods?

There are several sampling methods, including random sampling, stratified sampling, and cluster sampling. Each has its own advantages and disadvantages.

Can you explain random sampling?

Random sampling involves selecting individuals from a population in such a way that each individual has an equal chance of being chosen. This helps to reduce bias.

What about stratified sampling?

Stratified sampling divides the population into subgroups or strata, and then random samples are taken from each stratum. This ensures representation from all segments.

When should I use cluster sampling?

Cluster sampling is useful when populations are large and spread out. It involves dividing the population into clusters and then randomly selecting entire clusters.

Which method is the most reliable?

The reliability of a sampling method depends on the research context. Random sampling is often considered the gold standard, but stratified sampling can be more effective in certain situations.