Please register to participate in our discussions with 2 million other members - it's free and quick! Some forums can only be seen by registered members. After you create your account, you'll be able to customize options and access all our 15,000 new posts/day with fewer ads.
1. Random Sampling: A random sample is a sample in which every member of a population has an equal chance of being selected. As one can understand from the definition this method is not applicable to the results of processes because the population set should be static. In case of a process, the population set is dynamic and new and new results are constantly added to the data. Therefore one cannot ensure that every member has an equal chance of being selected. However the results of random sampling are amongst the best if adequate sample size is selected.
2. Stratified Random Sampling: In case of stratified random sampling, the population is broken down into strata which contain their own data elements. Within the strata, each data element has an equal chance of being selected. However the number of elements from each starta are pre-determined. This is close to random sampling. However, once again it cannot be used for a process because it requires a static population whereas a process is dynamic by definition.
Process Sampling Techniques
1. Systematic Sampling: In case of systematic sampling, the first element in the sample is chosen at random. Then the next elements are chosen in a systematic fashion. For example, the first element will be chosen at random then every tenth element will be included in the sample. Since these types of samples are systematic and do not need a static population base, they can be used for process sampling. In fact systematic sampling is one of the most popular methods used for process sampling.
2. Rational Subgrouping: Rational subgrouping is a sampling technique whose main aim is to produce data for control charts. Samples are drawn from subgroups at regular intervals. Hence the person who is collecting the sample needs to decide the sample size as well as the interval. This should be large enough to detect any changes in the underlying process.
Unintended bias can creep into process sampling if there is some ordering in the cases being sampled that is unknown. In general, random sampling is best (of course methods are usually only pseudo-random so should be closely examined for possible bias as well).
Stratified sampling is good for situtations where there are smaller subsamples within the sample that you don't want to miss, which is entirely possible using random sampling - so if you want to reliably report out on small subsamples you may need to over-sample them.
It mostly depends on your purpose - no one method is best all the time and your method may be limited by practical circumstances, which is where process sampling comes in because you may be limited by the manufacturing process and the fact that you can't wait until the entire batch is finished before you start sampling. Is your question based on a specific problem you're working on?
Unintended bias can creep into process sampling if there is some ordering in the cases being sampled that is unknown. In general, random sampling is best (of course methods are usually only pseudo-random so should be closely examined for possible bias as well).
Stratified sampling is good for situtations where there are smaller subsamples within the sample that you don't want to miss, which is entirely possible using random sampling - so if you want to reliably report out on small subsamples you may need to over-sample them.
It mostly depends on your purpose - no one method is best all the time and your method may be limited by practical circumstances, which is where process sampling comes in because you may be limited by the manufacturing process and the fact that you can't wait until the entire batch is finished before you start sampling. Is your question based on a specific problem you're working on?
Thanks for such a great information you've shared.
I would like to say Probability Sampling Techniques is best technique,Because his technique requires that the population is divided into two or more subgroups – based on a certain variable. The main motive of using this technique is to ensure that respondents from all exclusive subgroups are included at the time of the survey.
Thanks @davidsmith21
Please register to post and access all features of our very popular forum. It is free and quick. Over $68,000 in prizes has already been given out to active posters on our forum. Additional giveaways are planned.
Detailed information about all U.S. cities, counties, and zip codes on our site: City-data.com.
Please register to participate in our discussions with 2 million other members - it's free and quick! Some forums can only be seen by registered members. After you create your account, you'll be able to customize options and access all our 15,000 new posts/day with fewer ads.
