Sampling Technique : Probability Sampling

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Sampling technique is a technique of collecting sample. To determine the sample, there are several of sampling techniques used. Basically, there are two kinds of samples; Probability and Nonprobability Sampling.
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The definition of Probability Sampling is a sampling technique that provides the same opportunity for each element or member of the population to be selected as member of the sample. Probability samplings include: Simple Random Sampling, Proportionate Stratified Random Sampling, Disproportionate Stratified Random Sampling, Cluster Sampling (Area Sampling).
1. Simple Random Sampling
It is called simple because the sampling of the population is randomly without regard to existing strata in the population. It is done when the population is considered homogeneous. Simple random sampling can be done by lottery.
2. Proportionate Stratified Random Sampling
This technique is used when the population has members or elements that are not homogeneous and stratified proportionally. For example, the number of employees who pass S1 = 45, S2 = 30, senior high school = 50, junior high school = 100, elementary school = 500. The number of samples taken should include the educational strata.
3. Disproportionate Stratified Random Sampling
This technique is used to determine the number of samples, when the population is stratified but less proportionate. For example, the number of employees who pass S1 = 10, S2 = 5, S3 = 3, senior high school = 500, elementary school = 800, then the three graduates of S1, S2, S3 are taken as the samples, because this group is too small when compared to a group of senior high school and elementary school.
4. Cluster sampling (Area Sampling)
This technique is also called Regional Sampling Techniques. It is used to determine the sample when the object to be examined or the source of the data is very broad, for example, the population of a state, province or district. To determine what the population that will be a source of data, the sampling sets gradually from a wide area (state) to the smallest area (district). After that, the sample is selected randomly. 
For example, in a country, there are 30 provinces, and the sampling will use 15 provinces randomly. But remember that the provinces in a country are stratified (not same), so the sampling needs to use Stratified Random Sampling, There are densely populated in Province of Country, and there are not. Such characteristics need to be considered, so that the sampling according to the population strata can be determined. Area sampling technique is often used in two steps. The first step is determining the sample area, and the second step is determining those who are in that area by sampling.

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