What are the different sampling techniques and how do they compare?

What are the different sampling techniques and how do they compare?

There are several sampling techniques, including random sampling, stratified sampling, cluster sampling, and systematic sampling. Each has its strengths and weaknesses depending on the research context.

Can you explain random sampling and its advantages?

Random sampling involves selecting individuals from a population in such a way that each individual has an equal chance of being chosen. Its advantages include reducing bias and ensuring that the sample is representative of the population.

What about stratified sampling?

Stratified sampling divides the population into subgroups or strata and samples from each stratum. This technique ensures that specific subgroups are adequately represented, which can improve the accuracy of the results.

Are there any disadvantages to these techniques?

Yes, random sampling can be impractical if the population is large or hard to access, while stratified sampling requires detailed knowledge of the population structure, which may not always be available.