Talk:2001: Clickbait-Corrected p-Value

2018-06-02T01:39:00Z

Winstonewert:

I thought this comic was about ''correcting'' for any p-hacking that aimed to increase the media presence (and thus the clickbait) of the study. [[Special:Contributions/172.68.94.10|172.68.94.10]] 17:32, 1 June 2018 (UTC)

The explanation for null hypothesis is correct semantically, it would be accepted if there was no OR negative improvement, however, this is usually stated more succinctly as "will not improve performance" or (in keeping with the language of the comic) "does not boost performance", since that has the same meaning without the unnecessary verbosity. ---- {{unsigned ip|162.158.186.42}}

I can't believe I clicked on this [[Special:Contributions/172.68.86.46|172.68.86.46]] 20:28, 1 June 2018 (UTC)

I've removed a paragraph which claimed that this was an instance of Bayes theorem. Despite some similarity in structure, it is not. [[User:Winstonewert|Winstonewert]] ([[User talk:Winstonewert|talk]]) 01:39, 2 June 2018 (UTC)

2001: Clickbait-Corrected p-Value

2018-06-02T01:37:14Z

Winstonewert: Removing incorrect reference to Bayesian

{{comic
| number = 2001
| date = June 1, 2018
| title = Clickbait-Corrected p-Value
| image = clickbait_corrected_p_value.png
| titletext = When comparing hypotheses with Bayesian methods, the similar 'clickbayes factor' can account for some harder-to-quantify priors.
}}

==Explanation==
{{incomplete|Click here to learn more about the influence of Clickbait... But please first explain p-value. Most people don't know. And more wiki links.}}
This is yet another comic dealing with [[:Category:Clickbait|Clickbait]].

This comic references ''hypothesis testing'' in statistics. Hypothesis testing is a standard method to determine whether a particular hypothesis is supported by the data. Such tests compare sets of data to determine whether they are likely to be correlated. In the examples given in the comic, a researcher might compare data on athletic performance with data on chocolate consumption by those athletes to determine whether he two trend together. By convention, the "null hypothesis" (designated H0) is that there's no correlation (that chocolate doesn't improve athletic performance, in this case) and the "alternate hypothesis" (Ha) is that they are correlated (chocolate does improve athletic performance). These sets are subjected to statistical tests which return a "p-value" which is often misinterpreted as the probability that the null hypothesis is correct. Hence, if the p-value is low enough, the null hypothesis is rejected, and we conclude that the alternate hypothesis is supported by the data.

Actually, the p-value is the probability that one would get the results obtained, or any more extreme value, given that the null hypothesis is false. The misinterpretation of p-values as the probability that the null hypothesis is correct is a huge problem that lies at the source of a lot of confusion in the statistical interpretation of data.

In this version, the p-value is corrected by a factor which increases when readers click a headline stating that H1 is true, and decreases when people click a headline stating that H0 is true. This has the effect of ''increasing'' the p-value if readers favor H1 over H0, leading to a greater chance of ''H0'' being accepted. This seems to operate under the assumption that whatever clickers of clickbait believe, the reverse is likely to be true.

As the statistical results now depend on people's beliefs about the hypothesis, this is as far from actual science as one can get. However, in a way, it is more in tune with a quote by Arbuthnot (one of the originators of the use of p-values) attributing variation to active thought rather than chance, "From whence it follows, that it is Art, not Chance, that governs." Randall applying that quote to the thoughts of the masses, bringing it in line with "Art".

Clickbait is the practice of using deceptive or manipulative headlines to entice readers to click on a dubious news story, often with the purpose of generating ad revenue.

The comic does not present a correct example of null and alternative hypotheses. As the alternative hypothesis (H1) predicts that chocolate will '''improve performance''' (i.e., a one-tailed, directional hypothesis) the null hypothesis (H0) should predict that chocolate will '''do nothing''' or '''make performance worse'''. If, on the other hand, the alternative hypothesis (H1) was that chocolate would '''change performance''' (for better or worse; i.e., a two-tailed hypothesis) then the null hypothesis (H0) would be that chocolate would simply '''do nothing'''.

==Transcript==
:[Under a heading that says Clickbait-Corrected p-Value there is a mathematic formula. Below that is the description of the two used variables and what they mean:]
:Clickbait-corrected p-value:

:PCL = Ptraditional ∙ click(H1)/click(H0)

:H0: NULL hypothesis ("Chocolate has no effect on athletic performance")
:H1: Alternative hypothesis ("Chocolate boosts athletic performance")
:click(H): Fraction of test subjects who click on a headline announcing that H is true

{{comic discussion}}

[[Category:Clickbait]]
[[Category:Statistics]]

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Talk:2001: Clickbait-Corrected p-Value

2001: Clickbait-Corrected p-Value