Survey Sampling techniques

[imranmahmud]

Random sampling is the purest form of probability sampling. Each member of the population has an equal and known chance of being selected. When there are very large populations, it is often difficult or impossible to identify every member of the population, so the pool of available subjects becomes biased.

Systematic sampling is often used instead of random sampling. It is also called an Nth name selection technique. After the required sample size has been calculated, every Nth record is selected from a list of population members. As long as the list does not contain any hidden order, this sampling method is as good as the random sampling method. Its only advantage over the random sampling technique is simplicity. Systematic sampling is frequently used to select a specified number of records from a computer file.

Stratified sampling is commonly used probability method that is superior to random sampling because it reduces sampling error. A stratum is a subset of the population that share at least one common characteristic. Examples of stratums might be males and females, or managers and non-managers. The researcher first identifies the relevant stratums and their actual representation in the population. Random sampling is then used to select a sufficient number of subjects from each stratum. "Sufficient" refers to a sample size large enough for us to be reasonably confident that the stratum represents the population. Stratified sampling is often used when one or more of the stratums in the population have a low incidence relative to the other stratums.

Convenience sampling is used in exploratory research where the researcher is interested in getting an inexpensive approximation of the truth. As the name implies, the sample is selected because they are convenient. This nonprobability method is often used during preliminary research efforts to get a gross estimate of the results, without incurring the cost or time required to select a random sample.

Judgment sampling is a common nonprobability method. The researcher selects the sample based on judgment. This is usually and extension of convenience sampling. For example, a researcher may decide to draw the entire sample from one "representative" city, even though the population includes all cities. When using this method, the researcher must be confident that the chosen sample is truly representative of the entire population.

Quota sampling is the nonprobability equivalent of stratified sampling. Like stratified sampling, the researcher first identifies the stratums and their proportions as they are represented in the population. Then convenience or judgment sampling is used to select the required number of subjects from each stratum. This differs from stratified sampling, where the stratums are filled by random sampling.

Snowball sampling is a special nonprobability method used when the desired sample characteristic is rare. It may be extremely difficult or cost prohibitive to locate respondents in these situations. Snowball sampling relies on referrals from initial subjects to generate additional subjects. While this technique can dramatically lower search costs, it comes at the expense of introducing bias because the technique itself reduces the likelihood that the sample will represent a good cross section from the population.

Source: http://www.statpac.com/surveys/sampling.htm

NOTE:
For Probability sampling you can follow this formula, http://home.kku.ac.th/sompong/guest_speaker/KrejcieandMorgan_article.pdf

For non-probability or Convenience sampling (population unknown) you can use G* power calculator. http://www.ats.ucla.edu/stat/gpower/indepsamps.htm

[Tanvir Ahmed Chowdhury]

Nice Post

[anam]

Dear Sir
Probability and non probability sampling, which process is better and how we confirm it....

[saratasneem]

If the time frame can be properly designed, probabbility sampling is obviously better as it helps ta make inference more accurately.

[imranmahmud]

Hi
For random sampling , you need the list of population(Complete list). Example. If you are doing research on the employees of any specific organization. You can find out the exact number of population from their office.

If you do not have any list, then you can go for purposive or convenience sampling. Base on the statistical power of you research model , you can calculate your sample. I use g*power calculator (http://www.gpower.hhu.de/en.html).

Purposive sampling is now widely used. I have attached my recent paper for further reference. Please check the methodology (section 4)in the first paragraph. 

Thanks

[Saujanna Jafreen]

thank you sir for your sharing...... and also thanks goes to Imran sir, for explanation

[Bipasha Matin]

Thanks for sharing

[Nujhat Anjum]

Thanks for sharing.

[Nujhat Anjum]

Thanks for sharing.

[Nujhat Anjum]

Thanks for sharing.