Talk:Biased sample

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(to Martin) Hi, this is your namesake, Mrdice. I'm into the logical fallacies at the moment, and I noticed you moved some articles around. For example, you put the spotlight fallacy together with biased sample. Is it alright with you if I give each fallacy, however closely related it is to another, its own page? Most fallacies are in some way or another related to eachother, and if we're going to put similar ones together, it would be a huge job, even more so because some of them belong to different catagories at the same time. My idea is to give each one its own page, and then mention at the bottom of the page to which ones they're related. Mrdice 03:19, 2004 Feb 16 (UTC)

Contents 1 "At best, this means the people who care most about an issue will answer" 2 Some bad splitting occured here... 3 Cleaning up 4 Biased samples and parameter estimation

[edit] "At best, this means the people who care most about an issue will answer"

This isn't necessarily best; it can be quite the opposite. Those who care most aren't bound to be true reflections of the population, especially if there's more room or inclination for people to care (or not) one way than the other. I can imagine this: Some government proposal has already been given the green light or even just been implemented. Many people were in favour of it, but they are already set to get their way and so might not bother voting. OTOH those who are against the idea are likely to flood the poll in protest.

It's also possible that the statment of a poll can be biased, by stating only one side of the argument. I can imagine this leading to biased results.... -- Smjg 15:31, 17 Jun 2005 (UTC)

[edit] Some bad splitting occured here...

This article has turned into a childish description of one specific type of misuse of statistics. Biased sampling has many forms and is sometimes unavoidable, but when the type of bias in the sampling mechanism is known it can be taken into account and possibly corrected in the analysis (that is, one can draw inference for the unbiased population given a biased sample). So it needs a major rewrite I cannot provide at the time.--Boffob 18:23, 12 January 2007 (UTC)

[edit] Cleaning up

This could use an overhaul in spelling and grammar check. If it weren't so late I'd do it myself. I'll come around and do it sometime if no one else wants to. (forgot to sign my post!)Imasleepviking 13:46, 1 February 2007 (UTC)

[edit] Biased samples and parameter estimation

I don't have time to discuss it much now, but I want to mention that there are many methods that can take different forms of biased sampling into account (not just reweighting of badly balanced samples), and there are cases where ignoring the bias will still lead to consistent (if inefficient) estimates of the parameters of interest (or a subset of them). So saying that estimates will always be erroneous and that statistical methods always assume that samples are representative of the target population is simply untrue. Though I reverted some recent changes made by an anonymous IP, I agree that the "problems with biased samples" section needs some rewriting.--Boffob (talk) 01:35, 26 January 2008 (UTC)

This may sound like a quibble, but the article should not then say that any statistic calculated form a biased sample has the potential to be erroneous (I think that was part of the point of my edit, but I haven't checked). First of all, a stratified sample is classified by the article as a biased sample, and its accuracy can be estimated; in that sense it has no potential to be erooneous. Seondly, if by potential to be erroneous we mean that that the statistic calculated from a sample may be markedly different from the parameter, that is true of any sample, so it's not a distinguishing characteristic of biased samples. Perhaps the point could be that a confidence interval cannot be calculated.

I would also like to raise the issue of whether this article is needed in addition to Stratified sampling and Non-probability sample. Phrenesiac (talk) 00:29, 27 January 2008 (UTC)

I did write this in the hope to reword some contentious parts of the article. Of course, any estimation is bound to errors. The issue here is that ignoring biased sampling can lead to, surprise, surprise, asymptotically biased estimators of the parameters of interest, as opposed to consistent estimators, but there are actually cases where some parameters will be consistently estimated despite biased sampling. The other thing is that a biased sample is not necessarily a stratified sample (deliberate sampling method over well-defined strata, but stratified sampling may still have biased sampling issues) or a non-probability sample, as in many cases, the probability of sampling an individual from the target population can be computed, the issue is that it is not uniform over that target population (which would make it a random sample proper, and I realize that the Nonprobability sampling article does not define random sample properly). For example, length-biased sampled sampling and size-biased sampling have been studied extensively. So yes, this article is needed on top of the other two, it just needs some rewriting in a few places.--Boffob (talk) 01:43, 27 January 2008 (UTC)

I apologize for not paying attention to the changes to Nonprobability sampling. I believe that definition has changed a lot since last I looked closely at it. Anyway, we seem to be talking at cross-purposes here. I'll leave to you to make the necessary changes to this article. Though God knows how long they'll last. Phrenesiac (talk) 02:17, 27 January 2008 (UTC)

No need to apologize. I don't have the other two on my watchlist, so I haven't followed them. This one has been relatively stable since the last major rewrite that improved it a lot, so I haven't bothered with it so much, but there is some room for improvement, I'm just not sure how to rewrite this "erroneous" estimation bit without getting too technical.--Boffob (talk) 05:13, 27 January 2008 (UTC)