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Full reference, people!
A question that's been bothering me for some time: how does population size affect sample size for the same probability of precision? (I hope I asked this correctly.) Wblakesx
The proportion of sample size to population size is called the sampling fraction. Generally speaking, the precision depends on the absolute number of samples, taken and NOT the sampling fraction. Thus a sample of random of 1000 people is fine for estimating the views of a population of 60 million (as in the UK) but it would be almost equally good for estimating the views of a population of 600 million of 6 billion. Having said that, it's not quite true. As the sampling fraction becomes significant (greater than 5 or 10%, say) you do need to add a correction to your precision estimates. But it's a good question, because the layman's intuition that the sampling fraction must be large for the sample to be good is dead wrong! Blaise 22:09, 20 September 2005 (UTC)
What is random sampling ?
The first line of the Mechanical Sampling section reads:
Mechanical sampling does not occurs typically in sampling solids, liquids and gases, using devices such as grabs, scoops, thief probes, the coliwasa and riffle splitter.
This doesn't make any sense. I don't know anything about mechanical sampling so could someone who does please fix this? TooMuchMath 03:06, 15 May 2006 (UTC)==Indian invention of sampling in 1928== User:126.96.36.199 added this statement to the article: "Some say that sampling was invented in India in July 1928." Can anyone provide a source explaining this claim? I have removed it from the article for now. -- Avenue 13:17, 25 May 2006 (UTC)
- This claim does not proceed; Sampling is a intuitive concept and happens (by instinct) since the beggining of time. Also, there are records of use of previously planned samples since the XIX century.--Lucas Gallindo 20:06, 29 September 2006 (UTC)
Sampling is mentioned in the Bible.
 Now the leaders of the people lived in Jerusalem; and the rest of the people cast lots to bring one out of ten to live in Jerusalem the holy city, while nine tenths remained in the other towns.
Nehemiah 11. 1
Blaise 09:51, 16 February 2007 (UTC)
Population Versus Sampling Frame
Currently, the definition of population is ambiguous. Compare the sentence "A population can be defined as including all people or items with the characteristic one wishes to understand" with "Note also that the population from which the sample is drawn may not be the same as the population about which we actually want information". These two statements are in contradiction. If the population is all people with the characteristic we wish to understand how can it not be the same as the population about which we actually want information? There appears to be two different definitions, only one of which is directly expressed. One definition refers to the abstract set of items that one would like information about and the other refers to the items listed in the sampling frame. I think it is confusing to define the term "population" in only one manner and then use it in both.