Sampling MethodsDefining the Target PopulationCensus SampleWhy sample?Probability versus NonprobabilityRandom SamplingSystematic SamplingStratified SamplingConvenience SamplingJudgment SamplingQuota SamplingSnowball SamplingSampling MethodsDefining 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 samplingRandom SamplingRandom 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 sufficien t 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 sampleJudgment 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