SamplingMuhammad ShahidLecturer IIN

PopulationAll the inhabitants of a given country or area considered together; the number of inhabitants of a given country or area The population is all elements (individuals, objective, or substance) that meet certain criteria for inclusions in a study (Kerlinger, 1986).

Population

Target PopulationThe group from which the study population is selectedStudy PopulationThe group selected for investigationElements of a populationThe subject on which the measurement is collected

SamplingSampleA sample is a subset of the population that is selected for a particular study, and the members of a sample are the subjects.

Sampling

Sampling

The process of selecting a number from all the subjects

is a process of selecting subjects who are representative of the population being studied

Sampling frameList of Participants

Sampling TypeProbabilitySimple Random samplingStratified Random SamplingCluster samplingSystematic SamplingNon Probability Convenience samplingQuota SamplingPurposive samplingNetwork Sampling

Probability SamplingIs a method of sampling that utilizes some form of random selection. In order to have a random selection method, you must set up some process or procedure that assures that the different units in your population have equal probabilities of being chosen.

Simple Random SamplingObjectiveTo select n units out of N such that each unit has an equal chance of being selected. ProcedureUse a table of random numbers, a computer random number generator, or a mechanical device to select the sample.

Stratified Random Sample

A stratified random sample is one obtained by separating the population elements into non-overlapping groups, called strata, and then selecting a simple random sample from each stratum.

Systematic Random SamplingNumber the units in the population from 1 to N decide on the n (sample size) that you want or need k = N/n = the interval size randomly select an integer between 1 to k then take every kth unit

Systematic Random SamplingAll of this will be much clearer with an example. Let's assume that we have a population that only has N=100 people in it and that you want to take a sample of n=20. To use systematic sampling, the population must be listed in a random order. The sampling fraction would be f = 20/100 = 20% in this case, the interval size, k, is equal to N/n = 100/20 = 5.

Systematic Random SamplingNow, select a random integer from 1 to 5. In our example, imagine that you chose 4. Now, to select the sample, start with the 4th unit in the list and take every k-th unit (every 5th, because k=5). You would be sampling units 4, 9, 14, 19, and so on to 100 and you would wind up with 20 units in your sample.

Cluster SamplingDivide population into clusters (usually along geographic boundaries) Randomly sample clusters Measure all units within sampled clusters

Cluster Samplingis a probability sample in which each sample unit is a collection, or cluster, of elements.The first task in cluster sampling is to specify appropriate clusters. Elements within a cluster are often physically close together and hence tent to have similar characteristics.

Non Probability samplingConvenience samplingQuota SamplingPurposive samplingNetwork Sampling

Convenience samplingis 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 non-probability 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.

Quota SamplingIt uses a convenience sampling technique with added feature - a strategy to ensure the inclusion of subjects types who are likely to be underrepresented in the convenience sample e.g. ethnicity , Hindu religion in Pakistan

Quota sampling is the non-probability 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.

Purposive /Judgment Samplingis a common non-probability 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.

Network / Snowball Samplingis a special non-probability 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.

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