Talk:Data dredging

message: I think that the intro defines the most egregious case of data dredging, and not data dredging in general.
"The process of data dredging involves automatically testing huge numbers of hypotheses about a single data set by exhaustively searching"
This is not necessarily true.  If I test 4 hypotheses about a single data set, only one turns up significant and I report only that one hypothesis, then I have committed p-hacking/data-dredging.  This is an important distinction because this involved neither huge numbers of hypotheses nor an exhaustive search.
I'm going to let this sit for a day, and if nobody has objections, I will implement the changes. Ihearthonduras (talk) 18:45, 24 January 2018 (UTC)
thread_title:  Easing the verbiage of the Introduction 

message: I support the merge of this page with the page on Data Dredging. These are essentially the same concept by two different names. They should be on the same page. Maybe a disambiguation entry can be posted to differentiate these concepts. AjeetKhurana (talk) —Preceding undated comment added 13:58, 20 May 2009 (UTC)
thread_title:  Merge 

message: I don't think the global tag is justified: it's applied to an example of illegitimate hypothesis formation, but the example doesn't need to be universal!  Richard Pinch (talk) 18:57, 11 June 2008 (UTC)
replies: text: Well, it could certainly be rephrased in a more international manner, but I think the true problem is that the sentence is too long and not very clear, and doesn't bring a clear conclusion (why would it be wrong?) Calimo (talk) 15:11, 13 January 2009 (UTC)
thread_title:  Global tag justified? 

message: "Circumventing the traditional scientific approach of conducting an experiment without a hypothesis can lead to premature conclusions."
I believe the traditional scientific approach is to form a hypothesis before conducting an experiment, so the sentence should be rewritten to say, "Circumventing the traditional scientific approach by conducting an experiment without a hypothesis can lead to premature conclusions."
Unless someone knows better and objects, I will make the change. —Blanchette (talk) 06:57, 9 May 2011 (UTC)
replies: text: Done. —Blanchette (talk) 21:19, 20 May 2011 (UTC)
thread_title:  Circumventing the scientific approach? 

message: This article has been watered down since I last read it, apparently in an effort to cast the topic in a more "neutral" light. Just the opening paragraph, for instance, now says: "Data dredging ... is the use of data mining to uncover relationships in data." That does not seem sufficient to me at all. All data mining is used for uncovering relationsships in data; the paragraph is almost tautological. The opening paragraph should instead succintly define data dredging as it differs from other ways of using data. If I can find reasonable sources, I may go ahead and rewrite some of it.--Anders Feder (talk) 10:03, 4 September 2014 (UTC)
thread_title:  Vague 

message: I was thinking of using an image from this site as a headline image since it explains the idea really well (it's Creative Commons Attribution-licensed). Any thoughts on this, or suggestions for a particularly ridiculous one? Blythwood (talk) 22:48, 3 June 2015 (UTC)
thread_title:  Spurious Correlations 

message: The article appears to vague to me, too and combines multiple problems into one which should be separated. More thorough mathematical derivations would be helpful in my opinion. Some core statements are known to be wrong, although still frequently mentioned as urban legends in social sciences (e.g., testing multiple stochastically independent hypotheses on the same data set is no problem. That distinction is not made in the page so far). I suggest to rewrite.  — Preceding unsigned comment added by Timo von Oertzen (talk • contribs) 15:05, 30 January 2017 (UTC)
thread_title:  Second Vague, also second no merge 

message: I find the drawing conclusions from data section to be ridiculous and unsourced.
If it had been sourced we could maybe get to the bottom of the problems.  
For example, read Deming's "Red Bead experiment" from his The New Economics and then read this section. A p-chart will tell you that immediately that there is nothing there are no conclusions whatsoever that can be drawn from a sample of 5 coin flips.
2601:14F:8005:B810:C823:C430:769F:E823 (talk) 16:43, 21 October 2017 (UTC)
thread_title:  Drawing Conclusions from data section 

message: (Edited) The following paper had a considerable impact in experimental psychology and might be worth mentioning in the article.  One of its co-authors supposedly coined the term "p-hacking" though the term itself doesn't appear in the paper.  I'll try to add it sometime if nobody else does, but if someone else does it first, that's great.  Citation:
*  Simmons, Joseph P. and Nelson, Leif D. and Simonsohn, Uri, False-Positive Psychology: Undisclosed Flexibility in Data Collection and Analysis Allows Presenting Anything as Significant (May 23, 2011). Psychological Science, 2011. Available at SSRN: https://ssrn.com/abstract=1850704 
The authors wrote an invited retrospective 5 years later:
* Simmons, Joseph P. and Nelson, Leif D. and Simonsohn, Uri, False-Positive Citations (March 27, 2017). Perspectives on Psychological Science, Forthcoming. Available at SSRN: https://ssrn.com/abstract=2916240
173.228.123.121 (talk) 02:38, 5 March 2018 (UTC)
thread_title:  p-hacking 

message: *  Not sure where else to park this.  In most of the cases the fraud was lighter stuff like underreporting non-significant results but sometimes they were asked to actually falsify data. 173.228.123.166 (talk) 07:07, 3 November 2018 (UTC)
thread_title:  1 in 4 statisticians say they were asked to commit scientific fraud 

message: Regarding the sentence with much editing and discussion (in edit summaries).  It seems to me that the important point is getting results with an indication of statistical significance, while intentionally (usually) disregarding the truth. What might be called in a legal sense, wanton disregard for the truth.  If you do it long enough, you might (un)luckily find something actually true. Consider a politician at a campaign rally energizing his base with unsubstantiated claims, and without any interest in the truth.  Very rarely, he might accidentally say something true, but that is just random luck. Gah4 (talk) 01:49, 13 November 2019 (UTC)
thread_title:  ''thus dramatically increasing and understating the risk of false positives''