Sampling Methods.

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Presentation transcript:

Sampling Methods

Defining the Target Population It is critical to the success of the research project to clearly define the target population. Rely on logic and judgment. The population should be defined in connection with the objectives of the study.

Census Sample A census study occurs if the entire population is very small or it is reasonable to include the entire population (for other reasons). It is called a census sample because data is gathered on every member of the population.

Why sample? The population of interest is usually too large to attempt to survey all of its members. A carefully chosen sample can be used to represent the population. The sample reflects the characteristics of the population from which it is drawn.

Probability versus Nonprobability Probability Samples: each member of the population has a known non-zero probability of being selected Methods include random sampling, systematic sampling, and stratified sampling. Nonprobability Samples: members are selected from the population in some nonrandom manner Methods include convenience sampling, judgment sampling, quota sampling, and snowball sampling

Random Sampling 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’ to identify every member of the population, so the pool of available subjects becomes biased.

Systematic Sampling 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.

Stratified Sampling 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; such as males and females. Identify relevant stratums and their actual representation in the population. Random sampling is then used to select a sufficient number of subjects from each stratum. 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 Convenience sampling is used in exploratory research where the researcher is interested in getting an inexpensive approximation. The sample is selected because they are convenient. It is a nonprobability method. Often used during preliminary research efforts to get an estimate without incurring the cost or time required to select a random sample

Judgment Sampling Judgment sampling is a common nonprobability method. The sample is selected based upon judgment. an extension of convenience sampling When using this method, the researcher must be confident that the chosen sample is truly representative of the entire population.

Quota Sampling Quota sampling is the nonprobability equivalent of stratified sampling. First identify 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.

Snowball 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. This technique relies on referrals from initial subjects to generate additional subjects. It lowers search costs; however, it introduces bias because the technique itself reduces the likelihood that the sample will represent a good cross section from the population.