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Probability sampling techniques

Discuss Probability sampling techniques within the Marketing Research forums, part of the Resolve Your Query - Get Help and discuss Projects category; 1. Sampling units are selected by chance. 2. It is possible to pre-specify every potential sample of a given size ...

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Sunanda K. Chavan
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Probability sampling techniques - October 21st, 2010

1. Sampling units are selected by chance.
2. It is possible to pre-specify every potential sample of a given size that could be drawn from the population, as well as the probability of selecting each sample.
3. Every potential sample need not have the same probability of selection, but it is possible to specify the probability of selecting any particular sample of a given size.
4. This requires not only a precise definition of the target population, but also a general specification of the sampling frame. Because sample elements are selected by chance.
5. It is possible to determine the precision of the sample estimated of the characteristics of interest. Confidence intervals, which contain the true population value with a given level of certainty, can be calculated. This permits the researcher to make inferences of projections about the target population from which the sample was drawn. Probability sampling techniques are classified based on :
 Element versus cluster sampling
 Equal unit probability versus unequal probabilities
 Unstratified versus stratified selection
 Random versus systematic selection
 Single-stage versus multistage techniques
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Bhautik Kawa
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Re: Probability sampling techniques - February 23rd, 2016

Quote:
Originally Posted by sunandaC View Post
1. Sampling units are selected by chance.
2. It is possible to pre-specify every potential sample of a given size that could be drawn from the population, as well as the probability of selecting each sample.
3. Every potential sample need not have the same probability of selection, but it is possible to specify the probability of selecting any particular sample of a given size.
4. This requires not only a precise definition of the target population, but also a general specification of the sampling frame. Because sample elements are selected by chance.
5. It is possible to determine the precision of the sample estimated of the characteristics of interest. Confidence intervals, which contain the true population value with a given level of certainty, can be calculated. This permits the researcher to make inferences of projections about the target population from which the sample was drawn. Probability sampling techniques are classified based on :
 Element versus cluster sampling
 Equal unit probability versus unequal probabilities
 Unstratified versus stratified selection
 Random versus systematic selection
 Single-stage versus multistage techniques
Hello Sunanda,

It was really appreciable and i am sure it would help many people. Well, i found some important information Population and sample, Sampling techniques and wanna share it with you and other's. So please download and check it.
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File Type: pdf Population and sample, Sampling techniques.pdf (195.6 KB, 1 views)


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