Skip to main content

Authors - D

A-B-C-D-E-F-G-H-I-J-K-L-M-N-O-P-Q-R-S-T-U-V-W-X-Y-Z


Thibault Damour (with Mathieu Burniat)

Erich von Daniken

David Darling

David Darling (with Dirk Schulze-Makuch)

Kate Darling

Charles Darwin

Idrapamit Das

Laurent Daudet (with Appupen)

Paul Dauvergne

Romeel Davé

Thomas Davenport (with Steven Miller)

Paul Davies

Sally Davies

Daniel Davis

Richard Dawkins

Mark Stuart Day

Niall Deacon

David Deamer (with Wallace Kaufman)

Kees van Deemter

Ronald Deibert

Louis Del Monte

Mark Denny

John Derbyshire

Clément and Guillaume Deslandes

Adrian Desmond (with James Moore)

Guy Deutscher

Keith Devlin

Lee De-Wit

Iain Dey (with Douglas Buck)

Persi Diaconis (with Ron Graham)

Persi Diaconis (with Brian Skyrms)

Philip K. Dick

Andrew Dilnot (with Michael Blastland)

Thomas Disch

Douglas Dixon (with John Adams)

Cory Doctorow

Pieter van Dokkum

Paul Dolan

Pedro Domingos

Athene Donald

Michael Dowd

Neil Downie

Douwe Draaisma

Liam Drew

Karl Drinkwater

Sarah Dry

Marcus du Sautoy

Stephen Dubner (with Steven Levitt)

Comments

Post a Comment

Popular posts from this blog

Vector - Robyn Arianrhod ****

This is a remarkable book for the right audience (more on that in a moment), but one that's hard to classify. It's part history of science/maths, part popular maths and even has a smidgen of textbook about it, as it has more full-on mathematical content that a typical title for the general public usually has. What Robyn Arianrhod does in painstaking detail is to record the development of the concept of vectors, vector calculus and their big cousin tensors. These are mathematical tools that would become crucial for physics, not to mention more recently, for example, in the more exotic aspects of computing. Let's get the audience thing out of the way. Early on in the book we get a sentence beginning ‘You likely first learned integral calculus by…’ The assumption is very much that the reader already knows the basics of maths at least to A-level (level to start an undergraduate degree in a 'hard' science or maths) and has no problem with practical use of calculus. Altho
Post a Comment
Read more

Everything is Predictable - Tom Chivers *****

There's a stereotype of computer users: Mac users are creative and cool, while PC users are businesslike and unimaginative. Less well-known is that the world of statistics has an equivalent division. Bayesians are the Mac users of the stats world, where frequentists are the PC people. This book sets out to show why Bayesians are not just cool, but also mostly right. Tom Chivers does an excellent job of giving us some historical background, then dives into two key aspects of the use of statistics. These are in science, where the standard approach is frequentist and Bayes only creeps into a few specific applications, such as the accuracy of medical tests, and in decision theory where Bayes is dominant. If this all sounds very dry and unexciting, it's quite the reverse. I admit, I love probability and statistics, and I am something of a closet Bayesian*), but Chivers' light and entertaining style means that what could have been the mathematical equivalent of debating angels on
Post a Comment
Read more

The Art of Uncertainty - David Spiegelhalter *****

There's something odd about this chunky book on probability - the title doesn't mention the P word at all. This is because David Spiegelhalter (Professor Sir David to give him his full title) has what some mathematicians would consider a controversial viewpoint. As he puts it 'all probabilities are judgements expressing personal uncertainty.' He strongly (and convincingly) argues that while the mathematical approach to probability is about concrete, factual values, outside of the 'natural' probabilities behind quantum effects, almost all real world probability is a subjective experience, better described by more subjective terms like uncertainty, chance and luck. A classic way to distinguish between those taking the frequentist approach to probability and the Bayesian approach is their attitude to what the probability is of a fair coin coming up heads or tails after the coin has been tossed but before we have looked at it. The frequentist would say it's def
Post a Comment
Read more