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[http://election.princeton.edu/wp-content/uploads/autographics/EV_histogram_today-200px.png here]


http://election.princeton.edu/wp-content/uploads/autographics/EV_history.png


==Ghost Writing==
==Forsooth==


==Ghost Writing==
==Quotations==
“We know that people tend to overestimate the frequency of well-publicized, spectacular
events compared with more commonplace ones; this is a well-understood phenomenon in
the literature of risk assessment and leads to the truism that when statistics plays folklore,
folklore always wins in a rout.”
<div align=right>-- Donald Kennedy (former president of Stanford University), ''Academic Duty'', Harvard University Press, 1997, p.17</div>


Conspiracy theorists sometimes turn to statistics to prove their case.  Jack Cashill writing  [http://www.americanthinker.com/2008/10/who_wrote_dreams_from_my_fathe_1.html here] compares Barack Obama's book, Dreams From My Father, with Bill Ayers' book, Fugitive Days, in order to show that Ayers is the true author of Dreams From My Father.
----


Cashill writes, "To add a little science to the analysis, I identified two similar 'nature' passages in Obama's and Ayers' respective memoirs, the first from Fugitive Days:
"Using scientific language and measurement doesn’t prevent a researcher from conducting flawed experiments and drawing wrong conclusions — especially when they confirm preconceptions."
'I picture the street coming alive, awakening from the fury of winter, stirred from the chilly spring night by cold glimmers of sunlight angling through the city.'


The second from Dreams:
<div align=right>-- Blaise Agüera y Arcas, Margaret Mitchell and Alexander Todoorov, quoted in: The racist history behind facial recognition, ''New York Times'', 10 July 2019</div>


'Night now fell in midafternoon, especially when the snowstorms rolled in, boundless prairie storms that set the sky close to the ground, the city lights reflected against the clouds.'
==In progress==
[https://www.nytimes.com/2018/11/07/magazine/placebo-effect-medicine.html What if the Placebo Effect Isn’t a Trick?]<br>
by Gary Greenberg, ''New York Times Magazine'', 7 November 2018


These two sentences are alike in more than their poetic sense, their length and their gracefully layered structure.  They tabulate nearly identically on the Flesch Reading Ease Score (FRES), something of a standard in the field.  The 'Fugitive Days' excerpt scores a 54 on reading ease and a 12th grade reading level.  The 'Dreams' excerpt scores a 54.8 on reading ease and a 12th grade reading level.  Scores can range from 0 to 121, so hitting a nearly exact score matters."
[https://www.nytimes.com/2019/07/17/opinion/pretrial-ai.html The Problems With Risk Assessment Tools]<br>
by Chelsea Barabas, Karthik Dinakar and Colin Doyle, ''New York Times'', 17 July 2019


Cashill continues, "A more reliable data-driven way to prove authorship goes under the rubric 'cusum analysis' or QSUM.  This analysis begins with the measurement of sentence length, a significant and telling variable.  To compare the two books, I selected thirty-sentence sequences from Dreams and Fugitive Days, each of which relates the author's entry into the world of 'community organizing.' 'Fugitive Days' averaged 23.13 words a sentence.  'Dreams' averaged 23.36 words a sentence.  By contrast, the memoir section of [Cashill's] 'Sucker Punch' averaged 15 words a sentence."
==Hurricane Maria deaths==
Laura Kapitula sent the following to the Isolated Statisticians e-mail list:


Further, "Interestingly, the 30-sentence sequence that I pulled from Obama's conventional political tract, Audacity of Hope, averages more than 29 words a sentence and clocks in with a 9th grade reading level, three levels below the earlier cited passages from 'Dreams' and 'Fugitive Days.' The differential in the Audacity numbers should not surprise.  By the time it was published in 2006, Obama was a public figure of some wealth, one who could afford editors and ghost writers." 
:[Why counting casualties after a hurricane is so hard]<br>
:by Jo Craven McGinty, Wall Street Journal, 7 September 2018


===Discussion===
The article is subtitled: Indirect deaths—such as those caused by gaps in medication—can occur months after a storm, complicating tallies
Laura noted that
:[https://www.washingtonpost.com/news/fact-checker/wp/2018/06/02/did-4645-people-die-in-hurricane-maria-nope/?utm_term=.0a5e6e48bf11 Did 4,645 people die in Hurricane Maria? Nope.]<br>
:by Glenn Kessler, ''Washington Post'', 1 June 2018


1.  Go to the indispensible Wikipedia site [http://en.wikipedia.org/wiki/Flesch-Kincaid_Readability_Test here] to find
The source of the 4645 figure is a [https://www.nejm.org/doi/full/10.1056/NEJMsa1803972 NEJM article].  Point estimate, the 95% confidence interval ran from 793 to 8498.


Flesch Reading Ease<br>
President Trump has asserted that the actual number is
In the Flesch Reading Ease test, higher scores indicate material that is easier to read; lower numbers mark more-difficult-to-read passages. The formula for the Flesch Reading Ease Score (FRES) test is
[https://twitter.com/realDonaldTrump/status/1040217897703026689 6 to 18].
The ''Post'' article notes that Puerto Rican official had asked researchers at George Washington University to do an estimate of the death toll.  That work is not complete.
[https://prstudy.publichealth.gwu.edu/ George Washington University study]


        206.835 -1.015 *(total words/total sentences)
:[https://fivethirtyeight.com/features/we-still-dont-know-how-many-people-died-because-of-katrina/?ex_cid=538twitter We sttill don’t know how many people died because of Katrina]<br>
:by Carl Bialik, FiveThirtyEight, 26 August 2015
                  -84.6*(total syllables/total words)


----
[https://www.nytimes.com/2018/09/11/climate/hurricane-evacuation-path-forecasts.html These 3 Hurricane Misconceptions Can Be Dangerous. Scientists Want to Clear Them Up.]<br>
[https://journals.ametsoc.org/doi/abs/10.1175/BAMS-88-5-651 Misinterpretations of the “Cone of Uncertainty” in Florida during the 2004 Hurricane Season]<br>
[https://www.nhc.noaa.gov/aboutcone.shtml Definition of the NHC Track Forecast Cone]
----
[https://www.popsci.com/moderate-drinking-benefits-risks Remember when a glass of wine a day was good for you? Here's why that changed.]
''Popular Science'', 10 September 2018
----
[https://www.economist.com/united-states/2018/08/30/googling-the-news Googling the news]<br>
''Economist'', 1 September 2018


Here's the breakdown,
[https://www.cnbc.com/2018/09/17/google-tests-changes-to-its-search-algorithm-how-search-works.html We sat in on an internal Google meeting where they talked about changing the search algorithm — here's what we learned]
----
[http://www.wyso.org/post/stats-stories-reading-writing-and-risk-literacy Reading , Writing and Risk Literacy]


Score<br>
[http://www.riskliteracy.org/]
Notes
-----
   
[https://twitter.com/i/moments/1025000711539572737?cn=ZmxleGlibGVfcmVjc18y&refsrc=email Today is the deadliest day of the year for car wrecks in the U.S.]
90.0-100.0<br>
easily understandable by an average 11-year old student
   
60-70<br>
easily understandable by 13- to 15-year old students
   
0-30<br>
best understood by college graduates
   
Determine the FRES score for this Chance News wiki. Do likewise for Cashill's article.


Wikipedia goes on to state:
==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>


"[http://en.wikipedia.org/wiki/Reader's_Digest Reader's Digest magazine] has a readability index of about 65, [http://en.wikipedia.org/wiki/Time_magazine Time Magazine] scores about 52, and the [http://en.wikipedia.org/wiki/Harvard_Law_Review Harvard Law Review] has a general readability score in the low 30s. The highest (easiest) readability score possible is 121 (every sentence consisting of only one-syllable words); theoretically there is no lower bound on the score -- this sentence, for example, taken as a reading passage unto itself, has a readability score of ~21.9. This paragraph has a readability score of ~53.93."
<math>P(E)   = {n \choose k} p^k (1-p)^{ n-k}</math>


Verify the value of 53.93 which is very close to the 54 stated for each book.  Does this lend credence to Bill Ayers having written this paragraph? 
<math>\hat{p}(H|H)</math>


2. The same Wikipedia site has this to say about how FRES relates to grade level:
<math>\hat{p}(H|HH)</math>


An obvious use for readability tests is [http://en.wikipedia.org/wiki/Education in the field of education]. The "Flesch-Kincaid Grade Level Formula" translates the 0-100 score to a [http://en.wikipedia.org/wiki/U.S._grade_level U.S. grade level], making it easier for teachers, parents, librarians, and others to judge the readability level of various books and texts. It can also mean the number of years of education generally required to understand this text, relevant when the formula results in a number greater than 12. The grade level is calculated with the following formula:
==Accidental insights==
            0.39*(total words/total sentences) +
                  11.8*(total syllables/total words) -15.59


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.
<center>[[File:BrokenTile.jpg | 400px]]</center>
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.


<center>
{| class="wikitable"
|-
! 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%
|}
</center>
<center>[[File:Montante_plot1.png | 500px]]</center>
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.”


The result is a number that corresponds with a grade level. For example, a score of 8.2 would indicate that the text is expected to be understandable by an average student in 8th grade (usually aged 13-15 in the U.S.).
<center>[[File:Montante_plot2.png | 500px]]</center>
 
Determine the grade level for this Chance News wiki. Do likewise for Cashill's article.  Likewise for the Wikipedia paragraph.
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. [http://www.nature.com/news/2004/040227/full/news040223-11.html 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 [http://cran.r-project.org/web/packages/poweRlaw/vignettes/poweRlaw.pdf a vignette from CRAN] describing a maximum likelihood procedure for fitting a Power Law relationship. I am now learning my way through that.
3. Go [http://members.aol.com/qsums/QsumIntroduction.html here] for information about QSUM. Determine the QSUM for this Chance News wiki.  Do likewise for Cashill's article.


4. Speculate on how similar any two literary works would be as viewed by FRES and QSUM if the investigator had complete free reign over what segments to use.
Submitted by William Montante


Submitted by Paul Alper
----

Latest revision as of 20:58, 17 July 2019


Forsooth

Quotations

“We know that people tend to overestimate the frequency of well-publicized, spectacular events compared with more commonplace ones; this is a well-understood phenomenon in the literature of risk assessment and leads to the truism that when statistics plays folklore, folklore always wins in a rout.”

-- Donald Kennedy (former president of Stanford University), Academic Duty, Harvard University Press, 1997, p.17

"Using scientific language and measurement doesn’t prevent a researcher from conducting flawed experiments and drawing wrong conclusions — especially when they confirm preconceptions."

-- Blaise Agüera y Arcas, Margaret Mitchell and Alexander Todoorov, quoted in: The racist history behind facial recognition, New York Times, 10 July 2019

In progress

What if the Placebo Effect Isn’t a Trick?
by Gary Greenberg, New York Times Magazine, 7 November 2018

The Problems With Risk Assessment Tools
by Chelsea Barabas, Karthik Dinakar and Colin Doyle, New York Times, 17 July 2019

Hurricane Maria deaths

Laura Kapitula sent the following to the Isolated Statisticians e-mail list:

[Why counting casualties after a hurricane is so hard]
by Jo Craven McGinty, Wall Street Journal, 7 September 2018

The article is subtitled: Indirect deaths—such as those caused by gaps in medication—can occur months after a storm, complicating tallies

Laura noted that

Did 4,645 people die in Hurricane Maria? Nope.
by Glenn Kessler, Washington Post, 1 June 2018

The source of the 4645 figure is a NEJM article. Point estimate, the 95% confidence interval ran from 793 to 8498.

President Trump has asserted that the actual number is 6 to 18. The Post article notes that Puerto Rican official had asked researchers at George Washington University to do an estimate of the death toll. That work is not complete. George Washington University study

We sttill don’t know how many people died because of Katrina
by Carl Bialik, FiveThirtyEight, 26 August 2015

These 3 Hurricane Misconceptions Can Be Dangerous. Scientists Want to Clear Them Up.
Misinterpretations of the “Cone of Uncertainty” in Florida during the 2004 Hurricane Season
Definition of the NHC Track Forecast Cone

Remember when a glass of wine a day was good for you? Here's why that changed. Popular Science, 10 September 2018

Googling the news
Economist, 1 September 2018

We sat in on an internal Google meeting where they talked about changing the search algorithm — here's what we learned

Reading , Writing and Risk Literacy

[1]

Today is the deadliest day of the year for car wrecks in the U.S.

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>P(E) = {n \choose k} p^k (1-p)^{ n-k}</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

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