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A  [http://pss.sagepub.com/content/early/2015/08/25/0956797615597672.abstract psychology study] published earlier this year, reporting a link between emotional state and color perception, has now been retracted.  In particular, sadness was found to influence the perception of blues and yellows, but not reds and greens.  The story had received coverage in popular media.  For example see this [http://www.npr.org/sections/health-shots/2015/09/05/437477612/when-youve-got-the-blues-you-have-a-hard-time-seeing-blue story from NPR].  It originally aired on September 5, 2015, but was updated on November 5 to reflect the retraction.
A  [http://pss.sagepub.com/content/early/2015/08/25/0956797615597672.abstract psychology study] published earlier this year, reporting a link between emotional state and color perception, has now been retracted.  In particular, sadness was found to influence the perception of blues and yellows, but not reds and greens.  The story had received coverage in popular media.  For example see this [http://www.npr.org/sections/health-shots/2015/09/05/437477612/when-youve-got-the-blues-you-have-a-hard-time-seeing-blue story from NPR].  It originally aired on September 5, 2015, but was updated on November 5 to reflect the retraction.


Describing the, ''Retraction Watch'' quotes the following description of the error (citing [http://mindhacks.com/2015/10/03/statistical-fallacy-impairs-post-publication-mood/ MindHacks])
To explain the error, ''Retraction Watch'' quotes the following description from [http://mindhacks.com/2015/10/03/statistical-fallacy-impairs-post-publication-mood/ MindHacks]:
<blockquote>
<blockquote>
The flaw, anonymous comments suggest, is that a difference between the two types of colour perception is claimed, but this isn’t actually tested by the paper – instead it shows that mood significantly affects blue-yellow perception, but does not significantly affect red-green perception. If there is enough evidence that one effect is significant, but not enough evidence for the second being significant, that doesn’t mean that the two effects are different from each other. Analogously, if you can prove that one suspect was present at a crime scene, but can’t prove the other was, that doesn’t mean that you have proved that the two suspects were in different places.
The flaw, anonymous comments suggest, is that a difference between the two types of colour perception is claimed, but this isn’t actually tested by the paper – instead it shows that mood significantly affects blue-yellow perception, but does not significantly affect red-green perception. If there is enough evidence that one effect is significant, but not enough evidence for the second being significant, that doesn’t mean that the two effects are different from each other. Analogously, if you can prove that one suspect was present at a crime scene, but can’t prove the other was, that doesn’t mean that you have proved that the two suspects were in different places.

Revision as of 02:19, 16 November 2015

Colors and emotions

Paul Alper sent a link to the following:

Got the blues? You can still see blue: Popular paper on sadness, color perception retracted
by Alison McCook, Retraction Watch blog, 5 November 2015

A psychology study published earlier this year, reporting a link between emotional state and color perception, has now been retracted. In particular, sadness was found to influence the perception of blues and yellows, but not reds and greens. The story had received coverage in popular media. For example see this story from NPR. It originally aired on September 5, 2015, but was updated on November 5 to reflect the retraction.

To explain the error, Retraction Watch quotes the following description from MindHacks:

The flaw, anonymous comments suggest, is that a difference between the two types of colour perception is claimed, but this isn’t actually tested by the paper – instead it shows that mood significantly affects blue-yellow perception, but does not significantly affect red-green perception. If there is enough evidence that one effect is significant, but not enough evidence for the second being significant, that doesn’t mean that the two effects are different from each other. Analogously, if you can prove that one suspect was present at a crime scene, but can’t prove the other was, that doesn’t mean that you have proved that the two suspects were in different places.

Meat and cancer

Albert Kim sent a link to this story:

Beefing With the World Health Organization's Cancer Warnings


Diagnosing disease by smell

Miles Ott sent this link to the Isolated Statsticians list, with the description "A new 'lady tasting tea' example."

The amazing woman who can smell Parkinson’s disease — before symptoms appear
by Yanan Wang, Washington Post, 23 October 2015

This is the story of a Scottish woman named Joy Milne. Prior to her husband's diagnosis with Parkinson's disease, Milne's acute sense of smell led her to believe that something had changed with him. Was this just a coincidence, or a clue to early detection of Parkinson's?

An small experiment was conducted to find out (which, as Miles noted, is strongly reminiscent of Ronald Fisher's famous lady tasting tea example). Milne was presented with 12 T-shirts, 6 of which had been worn by known Parkinson's patients and 6 by controls. Milne reported that 7 of the shirts had the unusual smell. Six of these were from the Parkinson's patients, and one was a control. But it turned out that, months later, this last individual was diagnosed with Parkinson's!

Diet science

Are fats unhealthy? The battle over dietary guidelines
by Aaron E. Carroll, “Upshot” blog, New York Times, 12 October 2015.

Related “Upshot”: Behind new dietary guidelines, better science, February 23, 2015 <>

Earthquake prediction

Why a 99.9% earthquake prediction is 100% controversial
by Rong-Gong Lin II, Los Angeles Times, 23 October 2015

"This report

Donnellan added that the USGS' 85% probability and her 99.9% chance still favored a big earthquake in the next three years.

"If an earthquake happens in three years, we're both right," Donnellan said.

Some math doodles

<math>P \left({A_1 \cup A_2}\right) = P\left({A_1}\right) + P\left({A_2}\right) -P \left({A_1 \cap A_2}\right)</math>

<math>\hat{p}(H|H)</math>


<math>\hat{p}(H|HH)</math>

Accidental insights

My collective understanding of Power Laws would fit beneath the shallow end of the long tail. Curiosity, however, easily fills the fat end. I long have been intrigued by the concept and the surprisingly common appearance of power laws in varied natural, social and organizational dynamics. But, am I just seeing a statistical novelty or is there meaning and utility in Power Law relationships? Here’s a case in point.

While carrying a pair of 10 lb. hand weights one, by chance, slipped from my grasp and fell onto a piece of ceramic tile I had left on the carpeted floor. The fractured tile was inconsequential, meant for the trash.

BrokenTile.jpg

As I stared, slightly annoyed, at the mess, a favorite maxim of the Greek philosopher, Epictetus, came to mind: “On the occasion of every accident that befalls you, turn to yourself and ask what power you have to put it to use.” Could this array of large and small polygons form a Power Law? With curiosity piqued, I collected all the fragments and measured the area of each piece.

Piece Sq. Inches % of Total
1 43.25 31.9%
2 35.25 26.0%
3 23.25 17.2%
4 14.10 10.4%
5 7.10 5.2%
6 4.70 3.5%
7 3.60 2.7%
8 3.03 2.2%
9 0.66 0.5%
10 0.61 0.5%
Montante plot1.png

The data and plot look like a Power Law distribution. The first plot is an exponential fit of percent total area. The second plot is same data on a log normal format. Clue: Ok, data fits a straight line. I found myself again in the shallow end of the knowledge curve. Does the data reflect a Power Law or something else, and if it does what does it reflect? What insights can I gain from this accident? Favorite maxims of Epictetus and Pasteur echoed in my head: “On the occasion of every accident that befalls you, remember to turn to yourself and inquire what power you have to turn it to use” and “Chance favors only the prepared mind.”

Montante plot2.png

My “prepared” mind searched for answers, leading me down varied learning paths. Tapping the power of networks, I dropped a note to Chance News editor Bill Peterson. His quick web search surfaced a story from Nature News on research by Hans Herrmann, et. al. Shattered eggs reveal secrets of explosions. As described there, researchers have found power-law relationships for the fragments produced by shattering a pane of glass or breaking a solid object, such as a stone. Seems there is a science underpinning how things break and explode; potentially useful in Forensic reconstructions. Bill also provided a link to a vignette from CRAN describing a maximum likelihood procedure for fitting a Power Law relationship. I am now learning my way through that.

Submitted by William Montante