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Writing, Research, Applied Thinking and Applied Theory: Solutions with Interesting Implications, Problem Solving, Teaching and Research driven solutions
Explores writing, applications of thought and theory, solutions, engineering, design, DIY, Interesting approaches to problems, examples of interdisciplinary explorations and solutions.
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'The Most Significant And Least Appreciated Development In The History Of Our Species'

'The Most Significant And Least Appreciated Development In The History Of Our Species' | Writing, Research, Applied Thinking and Applied Theory: Solutions with Interesting Implications, Problem Solving, Teaching and Research driven solutions | Scoop.it

According to prominent Harvard psychologist Steven Pinker, statistics reveal dramatic reductions in war deaths, family violence, racism, rape, murder and all sorts of mayhem.

In his book, Pinker writes: "The decline of violence may be the most significant and least appreciated development in the history of our species."

And it runs counter to what the mass media is reporting and essentially what we feel in our guts.

Pinker and other experts say the reality is not painted in bloody anecdotes, but demonstrated in the black and white of spreadsheets and historical documents. They tell a story of a world moving away from violence.

Sharrock's insight:

Things are not as bad as the media is reporting. But improvements must continue to be made.

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SOCR: Statistics Online Computational Resource

In terms of selecting a statistical test, the most important question is "what is the main study hypothesis?" In some cases there is no hypothesis; the investigator just wants to "see what is there". For example, in a prevalence study there is no hypothesis to test, and the size of the study is determined by how accurately the investigator wants to determine the prevalence. If there is no hypothesis, then there is no statistical test. It is important to decide a priori which hypotheses are confirmatory (that is, are testing some presupposed relationship), and which are exploratory (are suggested by the data). No single study can support a whole series of hypotheses.

 
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FedStats

FedStats provides easy access to statistics and information produced by more than 100 U.S. Federal Government agencies
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How Long Will You Wait at the Emergency Room?

How Long Will You Wait at the Emergency Room? | Writing, Research, Applied Thinking and Applied Theory: Solutions with Interesting Implications, Problem Solving, Teaching and Research driven solutions | Scoop.it
How long you wait at the ER matters a lot. Our new interactive news application lets you see travel and wait times at hospital ERs near you.
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AllAnalytics - Beth Schultz - 7 Rules for Using HR Predictive Analytics

AllAnalytics - Beth Schultz - 7 Rules for Using HR Predictive Analytics | Writing, Research, Applied Thinking and Applied Theory: Solutions with Interesting Implications, Problem Solving, Teaching and Research driven solutions | Scoop.it
ConAgra analytics professionals lay down the law for using predictive analytics for employee purposes.
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Beyond Data Mining | BIG data, Data Mining, Pre...

Beyond Data Mining | BIG data, Data Mining, Pre... | Writing, Research, Applied Thinking and Applied Theory: Solutions with Interesting Implications, Problem Solving, Teaching and Research driven solutions | Scoop.it
In this article, author talks about the need for a change in the predictive modeling community’s focus and compares the four types of data mining: algorithm mining, landscape mining, decision mining, and discussion mining.
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Understanding Descriptive Statistics

Understanding Descriptive Statistics | Writing, Research, Applied Thinking and Applied Theory: Solutions with Interesting Implications, Problem Solving, Teaching and Research driven solutions | Scoop.it
This is an article about descriptive statistics
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Statistics Is Not Math: Update To Allow New Comments

Statistics Is Not Math: Update To Allow New Comments | Writing, Research, Applied Thinking and Applied Theory: Solutions with Interesting Implications, Problem Solving, Teaching and Research driven solutions | Scoop.it
Update Hello newcomers. Posts usually close for comments after two weeks. But since this one is getting so many views, I moved it up to re-open comments. "Here is a column of a couple of dozen numb...
Sharrock's insight:

This blog explores the differences between statistics as a discipline and mathematics. I started wondering why the two were referred to as separate. It turns out, they are different.

 

from the blog: "Statistics rightly belongs to epistemology, the philosophy of how we know what we know. Probability and statistics can even be called quantitative epistemology. Our axioms concern themselves with what probability means; that is, of the interpretation of uncertainty. But we abandon those axioms too quickly, choosing instead to follow the path of equations, nearly always skimping on what those equations actually mean."

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“Statisticians are the modern explorers.” An interview with Professor David J. Hand - Statistics Views

“Statisticians are the modern explorers.” An interview with Professor David J. Hand - Statistics Views | Writing, Research, Applied Thinking and Applied Theory: Solutions with Interesting Implications, Problem Solving, Teaching and Research driven solutions | Scoop.it

In the New Year’s Honours List for 2013, Professor David J. Hand was awarded an OBE for services to research and innovation. Earlier this year he was also appointed as a non-executive director of the UK Statistics Authority for a period of three years.

 

Professor Hand is currently Emeritus Professor of Mathematics at Imperial College, London. He was previously Professor of Statistics at Imperial College (1999-2011) during which time he was also Head of the Mathematics in Banking and Finance Programme (2005-09); before that he was Professor of Statistics at the Open University (1988-99). Since 2010, he has served as Chief Scientific Adviser to Winton Capital Management.

 

Sharrock's insight:

from the interview: "Both physicists and psychologists use the word ‘measurement’ but measuring IQ and measuring weight are very different notions; measuring pain and measuring height are also different. But in all these cases the same word is used."

 

It led to his writing a book "Measurement Theory and Practice: The World Through Quantification. ‘Pragmatic measurement’ is where you define what you are measuring and describe how to measure it simultaneously."

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Startup Business Failure Rate By Industry | Statistic Brain

Startup Business Failure Rate By Industry | Statistic Brain | Writing, Research, Applied Thinking and Applied Theory: Solutions with Interesting Implications, Problem Solving, Teaching and Research driven solutions | Scoop.it
Statistics and facts on business, consumer, sports, financials, world news
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Human Intelligence: Leon J. Kamin

"Kamin, being an expert statistician and methodologist, immediately became skeptical about the data and findings being reported by [Cyril] Burt. In order to become fully knowledgeable about both sides of the debate, Kamin then looked at the quintessential studies for the environmental argument and found their data and findings to be much more coherent and theoretically sound."

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Tufte's Invisible Yet Ubiquitous Influence

Tufte's Invisible Yet Ubiquitous Influence | Writing, Research, Applied Thinking and Applied Theory: Solutions with Interesting Implications, Problem Solving, Teaching and Research driven solutions | Scoop.it

"Clutter is a failure of design, not an attribute of information," Tufte writes in Envisioning Information.

Sharrock's insight:

excerpt: "Tufte's fame all flows from a rethinking of information design. He has consulted with IBM (IBM) on how to cultivate innovative thinking, helped The New York Times redo its information graphics and advised NASA on mission-critical software interface design. "[Tufte] has made it clear that in a cluttered Information Age we need methods of cutting through the brush," says Steven Heller, a design educator and critic who has been art director of both The New York Times Book Review and Screw magazine."

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▶ Is Punishment or Reward More Effective? - YouTube

 

 

The psychologist Daniel Kahneman, winner of the 2002 Nobel prize in economics, pointed out that regression to the mean might explain why rebukes can seem to improve performance, while praise seems to backfire.[8] http://en.wikipedia.org/wiki/Regression_toward_the_mean

 

 

I had the most satisfying Eureka experience of my career while attempting to teach flight instructors that praise is more effective than punishment for promoting skill-learning. When I had finished my enthusiastic speech, one of the most seasoned instructors in the audience raised his hand and made his own short speech, which began by conceding that positive reinforcement might be good for the birds, but went on to deny that it was optimal for flight cadets. He said, “On many occasions I have praised flight cadets for clean execution of some aerobatic maneuver, and in general when they try it again, they do worse. On the other hand, I have often screamed at cadets for bad execution, and in general they do better the next time. So please don’t tell us that reinforcement works and punishment does not, because the opposite is the case.” This was a joyous moment, in which I understood an important truth about the world: because we tend to reward others when they do well and punish them when they do badly, and because there is regression to the mean, it is part of the human condition that we are statistically punished for rewarding others and rewarded for punishing them. I immediately arranged a demonstration in which each participant tossed two coins at a target behind his back, without any feedback. We measured the distances from the target and could see that those who had done best the first time had mostly deteriorated on their second try, and vice versa. But I knew that this demonstration would not undo the effects of lifelong exposure to a perverse contingency.

http://en.wikipedia.org/wiki/Regression_toward_the_mean

Sharrock's insight:

Why do people resist research findings from areas like leadership, education, parenting, and other areas related to psychology and sociology? One reason may result from the confusion between the use and value of controlled experiments and the value of anecdotal evidence. 

 
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Sharrock's curator insight, January 11, 2014 4:49 PM

Why do people resist research findings from areas like leadership, education, parenting, and other areas related to psychology and sociology? One reason may result from the confusion between the use and value of controlled experiments and the value of anecdotal evidence. 

 

Sharrock's curator insight, January 11, 2014 4:50 PM

Why do people resist research findings from areas like leadership, education, parenting, and other areas related to psychology and sociology? One reason may result from the confusion between the use and value of controlled experiments and the value of anecdotal evidence. 

 
Sharrock's curator insight, January 11, 2014 4:50 PM

Why do people resist research findings from areas like leadership, education, parenting, and other areas related to psychology and sociology? One reason may result from the confusion between the use and value of controlled experiments and the value of anecdotal evidence. 

 
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A misunderstood statistic: 22 military veteran suicides a day

A misunderstood statistic: 22 military veteran suicides a day | Writing, Research, Applied Thinking and Applied Theory: Solutions with Interesting Implications, Problem Solving, Teaching and Research driven solutions | Scoop.it
In most discussions of suicide and the wars in Iraq and Afghanistan — including the online buzz that followed publication of a Times analysis on how young California veterans die — one statistic gets repeated most: 22 veterans kill themselves...

Via Bill Bentley
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Bill Bentley's curator insight, December 22, 2013 8:33 AM

Excellent example of misleading and irresponsibly reported statistics, this one on a sad topic.  Failing to understand data like this can lead to bad policy decisions.  

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Do High Food Prices Cause Social Unrest? | New Security Beat

Do High Food Prices Cause Social Unrest? | New Security Beat | Writing, Research, Applied Thinking and Applied Theory: Solutions with Interesting Implications, Problem Solving, Teaching and Research driven solutions | Scoop.it
the Blog of the Environmental Change and Security Program
Sharrock's insight:

The use of statistics to establish causation beyond corollation. Or not? 

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“The hungry statistician” – or why we never can get enough data ...

“The hungry statistician” – or why we never can get enough data ... | Writing, Research, Applied Thinking and Applied Theory: Solutions with Interesting Implications, Problem Solving, Teaching and Research driven solutions | Scoop.it
Why statisticians demand more data and are always hungry for more.
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Analytics 3.0 -- the old guard masters how to build data products

Analytics 3.0 -- the old guard masters how to build data products | Writing, Research, Applied Thinking and Applied Theory: Solutions with Interesting Implications, Problem Solving, Teaching and Research driven solutions | Scoop.it
Analytics 3.0, the 'data as a corporate asset' quiz and 'hellabytes': The Data Mill reports.
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Philosophy | William M. Briggs

William M. Briggs - Statistician to the Stars!
Sharrock's insight:

to read, perchance to...understand.

 

I want to read all of the articles here. I haven't though. His confidence in his understanding of statistics is infectious though. Amazing that one of his points is that there is no certainty. Teaching that statistics is a kind of applied epistmeology interests me. 

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Metadata - Wikipedia, the free encyclopedia

Metadata - Wikipedia, the free encyclopedia

The term metadata refers to " data about data". The term is ambiguous, as it is used for two fundamentally different concepts ( types). Structural metadata is about the design and specification of data structures and is more properly called "data about the containers of data"; descriptive metadata, on the other hand, is about individual instances of application data, the data content.

Sharrock's insight:

The exploration of metadata is valuable. People need to become aware of how metadata impacts our access, understanding, and use of data, to begin with. It will probably impact fields in the computer sciences in addition to data visualization, interdisciplinary studies, and other fields. 

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Big Data Could Create an Era of Big Discrimination

Big Data Could Create an Era of Big Discrimination | Writing, Research, Applied Thinking and Applied Theory: Solutions with Interesting Implications, Problem Solving, Teaching and Research driven solutions | Scoop.it
Personal data harvested by marketers is growing so vast and far reaching that it is threatening to unleash a new wave of digital discrimination, one that ordinary people won't even be able to see happening, Microsoft principal researcher Kate Crawford...
Sharrock's insight:

from the article: "A recent study at Cambridge University looking at almost 60,000 people’s Facebook “likes” was able to predict with high degrees of accuracy their gender, race, sexual orientation and even a tendency to drink excessively. The model could tell a gay man from a straight man correctly 88% of the time and predict race with 95% accuracy, for example. Government agencies, employers or landlords could easily obtain such data, Crawford warns."


and also, "Big data is not color blind, it's not gender blind and, in fact, marketers are using big data to have ever-more precise categories about you.”

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Lies, damned lies, statistics and inequality metrics

Lies, damned lies, statistics and inequality metrics | Writing, Research, Applied Thinking and Applied Theory: Solutions with Interesting Implications, Problem Solving, Teaching and Research driven solutions | Scoop.it
What is the best way to measure inequality? (Lies, damned lies, statistics and inequality metrics | Humanosphere http://t.co/HZAwfOTVu1)

Via João Greno Brogueira
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The differences between machine learning, data mining, and statistics

The differences between machine learning, data mining, and statistics | Writing, Research, Applied Thinking and Applied Theory: Solutions with Interesting Implications, Problem Solving, Teaching and Research driven solutions | Scoop.it

From machine learning to data mining. From statistics to probability. A lot of it seems similar, so what are the differences? Statistician William Briggs explains in an FAQ.


Via Sakis Koukouvis
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lajarre's curator insight, December 19, 2012 2:03 PM

Very good FAQ to get a quick grab on the terms you can hear around statistical data analytics.

Aurélia-Claire Jaeger's curator insight, December 20, 2012 4:33 AM

Une vision intéressante.

Extrait (traduit, enfin j'espère à peu près bien) : "Qu'est ce que le "Big Data" ? - Ce que l'on veut que ce soit, des données qui ne sont pas petites, un mot éphémère à la mode, une reconnaissance du fait qu'il est difficile de stocker et d'accéder à des bases de données volumineuses, un faux espoir (avec néanmoins parfois, fugitivement, des vérités lumineuses) que si les caractéristiques infimes sont connues et conservées à la microseconde près, on arrivera à prévoir tout ce qui concerne cette espèce imprévisible : les êtres humains."

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