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A collection of the many biographies of scientist Isaac Newton, demonstrating the ways in which his reputation continued to develop in the centuries after his death. It includes private letters, poetry and memoranda, and explores the debate over Newton's reputation, work and personal life.

A collection of the many biographies of scientist Isaac Newton, demonstrating the ways in which his reputation continued to develop in the centuries after his death. It includes private letters, poetry and memoranda, and explores the debate over Newton's reputation, work and personal life.

Newton's reputation was the subject of intense debate long before his death in 1727. While alive, numerous opponents sought to topple his theories, and his views on religion were considered by many to be unorthodox. For the vast majority of scholars, however, his groundbreaking approach to science overrode all else.
This book makes use of previously unpublished private writings and manuscript sources to present a concise exploration of the internal springs of Newton's complex character. Robert Iliffe describes Newton's studies in fields ranging from alchemy, physics, and mathematics, as...

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Enjoy Writing Your Science Thesis or Dissertation is a complete guide to good dissertation and thesis writing. It is written in an accessible style with cartoons and real-life anecdotes to liven up the text. It outlines the rules and conventions of scientific writing — particularly for dissertations and theses — and gives the reader practical advice about planning, writing, editing, presenting, and submitting a successful dissertation or thesis. Enjoy Writing Your Science Thesis or Dissertation can be used as either a guide from day...

This textbook presents the concepts and results underlying the Bayesian, frequentist, and Fisherian approaches to statistical inference, with particular emphasis on the contrasts between them. Aimed at advanced undergraduates and graduate students in mathematics and related disciplines, it covers basic mathematical theory as well as more advanced material, including such contemporary topics as Bayesian computation, higher-order likelihood theory, predictive inference, bootstrap methods, and conditional inference.