Talk:Spurious relationship

message: Hey, this isn't right, could someone fix it?  From the article:
> In practice, three conditions must be met in order to conclude that X causes Y, directly or indirectly:
>     * X must precede Y
>     * Y must not occur when X does not occur
>     * Y must occur whenever X occurs
> Spurious relationships can often be identified by considering whether any of these three conditions have been violated.
> The final condition may be relaxed in the case of indirect causation. 
Now rain (X) may cause me to stay in (Y); that is, I stay in whenever it rains, but I may stay in when it doesn't rain (because it may be snowing, for example).  So clearly there are obvious cases when the second condition may be relaxed, rather than the third.
In fact, the example of the pistol shot causing the death of the man doesn't even work, as the guy could die from a metiorite, thus violating the second condition, or he could be kept alive by the doctor, thus violating the third.  
The only condition that seems to be really relevant is the first.
So, what was actually meant here??
:I agree. "Y must not occur when X does not occur" is wrong. It's not necessary for Y to have only one possible cause. --75.49.223.247 (talk) 04:08, 23 June 2008 (UTC)
replies: text: I added an exception to the second condition covering this objection. I also added a second exception to the third condition and a note that the the conditions are necessary to prove causation but not sufficient. I may have gone a bit off-topic on the latter. MacMog (talk) 00:53, 3 March 2011 (UTC)

text: You're right -- I'll work on it. Thanks! Duoduoduo (talk) 17:10, 27 April 2011 (UTC)
thread_title: Error in this Article

message: Again, referring to the following:
> In practice, three conditions must be met in order to conclude that X causes Y, directly or indirectly:
>     * X must precede Y
>     * Y must not occur when X does not occur
>     * Y must occur whenever X occurs
The second condition indicates that X is a necessary condition for Y.  Then it is "relaxed", indicating that it is not necessary that X be a necessary condition for Y.
The third condition indicates that X is a sufficient condition for Y.  It is also relaxed, so it is not necessary that X be a sufficient condition for Y.
Finally the article says that the conditions above are necessary (not true, due to the relaxing) but not sufficient.  This section was a nice thought, but its claim to define causality falls flat.  — Preceding unsigned comment added by Arual kiram (talk • contribs) 16:06, 27 April 2011 (UTC)
replies: text: You're right -- I'll work on it. Thanks! Duoduoduo (talk) 17:10, 27 April 2011 (UTC)
thread_title: Further on error

message: I would agree that this should be combined with "Spurious Relationship", as this page only recites a different version (with a few extra comments) on the ice cream example mentioned in "Spurious Relationship: General Example". It might also work to change "General Example" to "Joint Effect", and insert the text from "Joint Effect" in its place.
Retrieved from "http://en.wikipedia.org/wiki/Talk:Joint_effect"
I took the step of deleting the redundant text in "joint effect" and redirecting to this entry. - Aug 28 2006
I removed the 'mergewith' tag, now the merge is complete. Terraxos 21:51, 2 September 2006 (UTC)
thread_title:  Combine "Spurious Relationship" and "Joint Effect" 

message: Should this stub be merged here? A correlecation is a subtype of a relationship, I'd think.-- Piotr Konieczny aka Prokonsul Piotrus | talk  17:25, 27 September 2006 (UTC)
thread_title: [[Spurious correlation]]

message: This article appears to confuse *confounding* with *spurious regression*.  Spurious regression can arise when time series variables are regressed against each other, even when there i sno confounding.  (For example, regressing two statistically independent random walks against each other can produce "statistically significant" correlations, simply because such series have trends.)  See http://www.econ.ku.dk/metrics/Econometrics2_05_II/Slides/10_cointegration_2pp.pdf.   —Preceding unsigned comment added by 172.190.11.4 (talk) 17:15, 4 February 2011 (UTC)
thread_title: Confuses *confounding* with *spurious regression*

message: The article says that Höfer found that "the number of clinical deliveries was inversely linked with the rise in stork population".  This is not accurate.  Höfer found "there is no correlation between deliveries in hospital buildings (clinical deliveries)".  No correlation is not the same as an inverse correlation.  I have corrected the article.  Kmasters0 (talk) 12:06, 5 March 2013 (UTC)
thread_title: Incorrect interpretation of Höfer's paper