Examples of using Probability sampling in English and their translations into Greek
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Equal and non equal probability sampling.
In probability sampling each element of the population has a known non-zero chance of being selected.
Bit By Bit- Asking questions- 3.4.1 Probability sampling: data collection and data analysis.
Currently, the dominant approach to sampling for social research is probability sampling.
The alternative to probability sampling is non-probability sampling.
This second era, roughly from 1960- 2000,was characterized by random digit dialing(RDD) probability sampling and telephone interviews.
The advantage of probability sampling is that sampling error can be calculated.
The first era of survey research was characterized by area probability sampling and face-to-face interviews.
The digital age is making probability sampling in practice harder and is creating new opportunities for non-probability sampling. .
The Horvitz-Thompson estimator is extremely useful because it leads to unbiased estimates for any probability sampling design(Horvitz and Thompson 1952).
Over time, the differences between probability sampling in theory and probability sampling in practice have been increasing.
Traditional solicitation modes, such as telephone or mail invitations to web surveys,can help overcoming probability sampling issues in online surveys.
Online panels can use either probability sampling or non-probability sampling. .
In probability sampling, all members of the target population have a known, nonzero probability of being sampled, and all people who are sampled respond to the survey.
Of course, it would be better to do perfectly executed probability sampling, but that no longer appears to be a realistic option.
In particular, probability sampling has been getting hard to do in practice, and non-probability sampling has been getting faster, cheaper, and better.
Sometimes researchers want a quick and rigid rule(e.g.,always use probability sampling methods), but it is increasingly difficult to offer such a rule.
For example, by using non-probability methods theCooperative Congressional Election Study(CCES) is able to have roughly 10 times more participants than earlier studies using probability sampling.
In the future, I expect that non-probability sampling will get better and cheaper while probability sampling will get worse and more expensive.
By way of exception, paragraphs 1 to 3 shall apply in Germany exclusively to the part of the sample based on probability sampling according to Article 8 of the Regulation of the European Parliament and of the Council(EC) No 1177/2003 concerning.
There are a variety of styles of non-probability sampling methods, butthe one thing that they have in common is that they cannot easily fit in the mathematical framework of probability sampling(Baker et al. 2013).
The second reason why researchers should reconsider non-probability sampling is because probability sampling in practice are become increasingly difficult.
Researchers face a difficult choice between probability sampling methods in practice-which are increasingly expensive and far from the theoretical results that justify their use-and non-probability sampling methods-which are cheaper and faster, but less familiar and more varied.
At the same time that there has been growing difficulties for probability sampling methods, there has also been exciting developments in non-probability sampling methods.
Classic book-length treatment of standard probability sampling and estimation are Lohr(2009)(more introductory) and Särndal, Swensson, and Wretman(2003)(more advanced).
Going forward, if you are trying to decide between using a probability sampling approach and a non-probability sampling approach you face a difficult choice.
In conclusion, this section has provided a model for probability sampling with non-response and shown the bias that nonresponse can introduce both without and with post-stratification adjustments.
The main difference between probability andnon-probability sampling is that with probability sampling everyone in the population has a known probability of inclusion.
Although both approaches were used in the early days of sampling, probability sampling has come to dominate, and many social researchers are taught to view non-probability sampling with great skepticism.
Thus, it is important to distinguish between probability sampling in theory,which has strong theoretical guarantees, and probability sampling in practice, which offers no such guarantees and depends on a variety of statistical adjustments.