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Naked Statistics: Stripping the Dread from…
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Naked Statistics: Stripping the Dread from the Data (original: 2013; edição: 2014)

de Charles Wheelan (Autor)

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6311327,463 (3.82)7
Demystifies the study of statistics by stripping away the technical details to examine the underlying intuition essential for understanding statistical concepts.
Membro:RobinTG
Título:Naked Statistics: Stripping the Dread from the Data
Autores:Charles Wheelan (Autor)
Informação:W. W. Norton & Company (2014), Edition: 1, 304 pages
Coleções:Sua biblioteca
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Etiquetas:Nenhum(a)

Detalhes da Obra

Naked Statistics: Stripping the Dread from the Data de Charles Wheelan (2013)

Adicionado recentemente porbiblioteca privada, LuannNelson, ejmw, toddymalone, ICS_LIbrary, Matt_0029, ntaylorwoods, edickey, nikkiroy, kotelnicki10
Bibliotecas HistóricasTim Spalding
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    A Field Guide to Lies: Critical Thinking in the Information Age de Daniel J. Levitin (PuddinTame)
    PuddinTame: Daniel J. Levitan particularly recommended this book in his own.
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Mostrando 1-5 de 13 (seguinte | mostrar todas)
Quite comprehensive and a good introduction to statistics. Previous to this book, I had little to no understanding of the practical applications of statistics, so this was a great read.
The only reason I rated it 4 instead of 5 is because some of the "humor" in the book wasn't funny. ( )
  nikkiroy | Apr 14, 2021 |
I love collecting data about myself, and I thought this book would enable me to put it to good use. Besides, we live in the age of big data, and what use is data if we can't do some magic with it.
So these are the two reasons why I decided to read this book. That would have been good in itself, but I got so much more than that! :)
It delved into research methodologies as well. As a result, I can say that I'm slightly better equipped to evaluate a given research which I'd have otherwise accepted blindly.

On to some of the concepts that truly blew my mind:
1. Positive publication bias: according to which, positive findings are more likely to be published than negative findings.
one important recurring idea in statistics is that unusual things happen every once in a while, just as a matter of chance. If you conduct 100 studies, one of them is likely to turn up results that are pure nonsense—like a statistical association between playing video games and a lower incidence of colon cancer. Here is the problem: The 99 studies that find no link between video games and colon cancer will not get published, because they are not very interesting. The one study that does find a statistical link will make it into print and get loads of follow-on attention.
2. Reverse causality: A statistical association between A and B does not prove that A causes B. In fact, it’s entirely plausible that B is causing A.
3. Central limit theorem: which is described as "the LeBron James of statistics—if LeBron were also a supermodel, a Harvard professor, and the winner of the Nobel Peace Prize." Its basic premise being: a large, properly drawn sample will resemble the population from which it is drawn.

Some other stuff I found to be interesting:
● It was interesting to read how statistics have the power to influence human behaviour by providing incentives, intentional or otherwise.
Especially the part where he tells about the time heart doctors had a "scorecard" that evaluated the mortality rates for the patients of cardiologists performing coronary angioplasty.
the scorecard, which ostensibly serves patients, can also work to their detriment: 83 percent of the cardiologists surveyed said that, because of the public mortality statistics, some patients who might benefit from angioplasty might not receive the procedure; 79 percent of the doctors said that some of their personal medical decisions had been influenced by the knowledge that mortality data are collected and made public. The sad paradox of this seemingly helpful descriptive statistic is that cardiologists responded rationally by withholding care from the patients who needed it most.
● Loved the part where he explained why it doesn't make sense to screen the entire population for a rare disease.
Suppose we can test for some rare disease with a high degree of accuracy. For the sake of example, let’s assume the disease affects 1 of every 100,000 adults and the test is 99.9999 percent accurate. The test never generates a false negative (meaning that it never misses someone who has the disease); however, roughly 1 in 10,000 tests conducted on a healthy person will generate a false positive, meaning that the person tests positive but does not actually have the disease. The striking outcome here is that despite the impressive accuracy of the test, most of the people who test positive will not have the disease.


● The part where credit card companies can ascertain to a reasonable degree whether you'll default on your next payment by simply looking at your past purchases.
“People who bought cheap, generic automotive oil were much more likely to miss a credit-card payment than someone who got the expensive, name-brand stuff. People who bought carbon-monoxide monitors for their homes or those little felt pads that stop chair legs from scratching the floor almost never missed payments. Anyone who purchased a chrome-skull car accessory or a ‘Mega Thruster Exhaust System’ was pretty likely to miss paying his bill eventually.”

As much as I want to give it a perfect 5, I can't. As a work of literature, I'd say this book has a large room for improvement, but I'd forgive it considering that it made a "boring" subject, such as statistics, fun to read!

PS: I DID THE MATH!

True to my word, I immediately set about to tweaking a sample of my Japanese learning data collected over a period of hundred days:


Lo and behold! The ubiquitous normal distribution in all its glory (well almost!).


The unusual bump on the left can be explained by the fact that on many days I would just revise, without learning any new words.
( )
  Govindap11 | Mar 21, 2020 |
Avoiding, based on my reaction to "Naked Economics" and a quick scan of the book in the library. Not enough substance and too much attitude.
  themulhern | Jul 21, 2019 |
This book was ok. I did learn quite a few things. But the humour was a bit cheesy and I'm not entirely convinced that someone who has never done statistics would understand it all. There are quite a few terms I came across that I think should be have been explained. I guess it depends on the audience this book was aimed at. There was a surprisingly high percentage of words compared to diagrams and illustrations. I thought that a more visual approach would have been helpful for a lot of the material. Wheelan does have quite a good capacity to explain things using words, though. I wouldn't say the book was riveting but was better than some of the books I've looked at on statistics. I'm no expert on statistics so can't say how accurate it all was. So I'll leave that to others. ( )
  spbooks | Aug 4, 2018 |
Not bad as far as pop math goes, a bit wordy. The hardee har har humor grates. ( )
  encephalical | Apr 27, 2018 |
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Nome do autorFunçãoTipo de autorObra?Status
Charles Wheelanautor principaltodas as ediçõescalculado
Davis, JonathanNarradorautor secundárioalgumas ediçõesconfirmado
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Demystifies the study of statistics by stripping away the technical details to examine the underlying intuition essential for understanding statistical concepts.

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