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Re: st: Explaining the Use of Inferential Statistics Even Though I Have Population Data


From   Salima Bouayad Agha <Salima.Bouayad-Agha@univ-lemans.fr>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Explaining the Use of Inferential Statistics Even Though I Have Population Data
Date   Sat, 30 May 2009 22:15:40 +0200

Well, even if is not really a stata question, I Think that the question of your reviewer is not obvious. In statistics a sample can effectively be a part of the population, and it is the most useful and current way to talk about of a sample, but in mathematical statistical course students also learn that a sample can be just the population a one specific moment of time and that this population can be very different if something else (random phenomenon) happens. Think for example of time series or some staistical process, let for example talk about the population of computers produced by a firm. So I'm not sure that your answer is the best one, depending on which field of research you are working. Just take a few moment to review some theoretical books on xaht is a sample in statistics.

Salima

PS :
In mathematical terms, given a random variable X with distribution F, a sample of length n\in\mathbb{N} is a set of n independent, identically distributed (iid) random variables with distribution F. It concretely represents n experiments in which we measure the same quantity. For example, if X represents the height of an individual and we measure n individuals, Xi will be the height of the i-th individual. Note that a sample of random variables (i.e. a set of measurable functions) must not be confused with the realisations of these variables (which are the values that these random variables take). In other words, Xi is a function representing the mesure at the i-th experiment and xi = Xi(?) is the value we actually get when making the measure.




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