Página inicialGruposDiscussãoMaisZeitgeist
Pesquise No Site
Este site usa cookies para fornecer nossos serviços, melhorar o desempenho, para análises e (se não estiver conectado) para publicidade. Ao usar o LibraryThing, você reconhece que leu e entendeu nossos Termos de Serviço e Política de Privacidade . Seu uso do site e dos serviços está sujeito a essas políticas e termos.
Hide this

Resultados do Google Livros

Clique em uma foto para ir ao Google Livros

How to Make the World Add Up: Ten Rules for…

How to Make the World Add Up: Ten Rules for Thinking Differently About… (edição: 2021)

de Tim Harford (Autor)

MembrosResenhasPopularidadeAvaliação médiaConversas
924234,424 (4.29)Nenhum(a)
Título:How to Make the World Add Up: Ten Rules for Thinking Differently About Numbers
Autores:Tim Harford (Autor)
Informação:The Bridge Street Press (2021), Edition: 01, 352 pages
Coleções:Sua biblioteca

Detalhes da Obra

How to Make the World Add Up de Tim Harford


Registre-se no LibraryThing tpara descobrir se gostará deste livro.

Ainda não há conversas na Discussão sobre este livro.

Exibindo 4 de 4
I am a huge fan of 'More or Less', the radio show/podcast presented by Tim Harford and so was keen to read this book. It didn't disappoint. There have been some reviews opining that Harford is the British Malcolm Gladwell and I can see the comparison but that does not make Harford's work any less valuable. For someone who loves statistics and the stories they can tell, this book is dynamite! ( )
  pluckedhighbrow | Jul 8, 2021 |
More uneven than Harford's other books, but still recommended.

Intro: How to lie with statistics. Harford used to love How to lie with statistics by Darrel Huff, but later found it too cynical. Duff's association with evidence-suppressing tobacco companies did not help. Statistics is not all about lying.
Rule 1: Search your feelings. It is easy to be fooled by feelings and conformity pressures. The story about how art critic and Vermeer expert Abraham Bredius in 1937 was fooled into declaring a fake painting Vermeer's "masterpiece". The fraudster van Meegeren had known how to tick the old expert's boxes. After having collaborated with the Nazi occupants during WWII, he did the same with the public's boxes, and was celebrated as a hero.
2. Ponder your personal experience. It is often good to see things up close. Ex.: Transport statistics, everyone travels at crowded times. But statistics like the average can also be misleading.
3. Avoid premature enumeration. Understand what we want to measure.
4. Step back and enjoy the view. Comparison and perspective.
5. Get the back story.
6. Ask who is missing. Good point, but I'm not sure looking for potholes with iphones is a good example, did people really think that all all the iphones was important and not realize that the potholes were the real data that was interesting. Discussion of N = all, goes to Netflix, etc., but administrative registries, which could perhaps more easily have opened up a discussion of counterfactuals and observations from possible worlds missing, which are important in research.
7. Demand transparency when the computer says 'no'. Algorithms. The example with Target that identified a woman as pregnant not good, pretty obvious that that is easy to predict from someone shopping patterns. Nice perspective on alchemy, did it persist for so long because of lack of scientific collaboration, in contrast to results of experiments on height and air pressure, e.g. Newton Boyd? Parallel today in algorithms, much secrecy and little accountability. Require transparency, rct, independent evaluation, data sharing?
8. Don't take the statistical bedrock for granted. Official statistics important, and many statisticians have defended them heroically under political pressure.
9. Remember that misinformation can be beautiful too. Easy to be fooled.
10. Keep an open mind. Learn and change, like Keynes and Tetlock's superforcasters.
The golden rule: Be curious. ( )
  ohernaes | Feb 19, 2021 |
Like Gladwell if Gladwell was humble, witty, and probably true. Hardford is refreshingly skeptical about his own "turns out…" tendencies. The book is larded with great little quotes and turns of phrase, and when I got to the end I somehow felt this was not just a tour of statistical thinking but a philosophy of life: be curious, question assumptions, don't be a cynic, look for what's left out. Encouragement in these depressing times. ( )
  adzebill | Dec 13, 2020 |
Engaging guide to statistical thinking, with some interesting stories to illustrate the 'rules' to make the world add up. ( )
  Amirani | Nov 13, 2020 |
Exibindo 4 de 4
sem resenhas | adicionar uma resenha
Você deve entrar para editar os dados de Conhecimento Comum.
Para mais ajuda veja a página de ajuda do Conhecimento Compartilhado.
Título canônico
Título original
Títulos alternativos
Data da publicação original
Lugares importantes
Eventos importantes
Filmes relacionados
Primeiras palavras
Últimas palavras
Aviso de desambiguação
Editores da Publicação
Autores Resenhistas (normalmente na contracapa do livro)
Idioma original
CDD/MDS canônico
Canonical LCC

Referências a esta obra em recursos externos.

Wikipédia em inglês


Não foram encontradas descrições de bibliotecas.

Descrição do livro
Resumo em haiku

Capas populares

Links rápidos


Média: (4.29)
3 1
3.5 1
4 5
5 5

É você?

Torne-se um autor do LibraryThing.


Sobre | Contato | LibraryThing.com | Privacidade/Termos | Ajuda/Perguntas Frequentes | Blog | Loja | APIs | TinyCat | Bibliotecas Históricas | Os primeiros revisores | Conhecimento Comum | 162,322,708 livros! | Barra superior: Sempre visível