Complete Probability Statistics 1 For Cambridge International As A Level


Download Complete Probability Statistics 1 For Cambridge International As A Level PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Complete Probability Statistics 1 For Cambridge International As A Level book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.

Download

Complete Probability & Statistics 1 for Cambridge International AS & A Level


Complete Probability & Statistics 1 for Cambridge International AS & A Level

Author: James Nicholson

language: en

Publisher: Oxford University Press - Children

Release Date: 2019-09-05


DOWNLOAD





Providing complete syllabus support (9709), this stretching and practice-focused course builds the advanced skills needed for the latest Cambridge assessments and the transition to higher education. Engaging, real world examples make mathematics relevant to real life.

Complete Probability & Statistics 2 for Cambridge International AS & A Level


Complete Probability & Statistics 2 for Cambridge International AS & A Level

Author: James Nicholson

language: en

Publisher: Oxford University Press - Children

Release Date: 2019-09-05


DOWNLOAD





Providing complete syllabus support (9709), this stretching and practice-focused course builds the advanced skills needed for the latest Cambridge assessments and the transition to higher education. Engaging, real world examples make mathematics relevant to real life.

E. T. Jaynes: Papers on Probability, Statistics and Statistical Physics


E. T. Jaynes: Papers on Probability, Statistics and Statistical Physics

Author: R.D. Rosenkrantz

language: en

Publisher: Springer Science & Business Media

Release Date: 2012-12-06


DOWNLOAD





The first six chapters of this volume present the author's 'predictive' or information theoretic' approach to statistical mechanics, in which the basic probability distributions over microstates are obtained as distributions of maximum entropy (Le. , as distributions that are most non-committal with regard to missing information among all those satisfying the macroscopically given constraints). There is then no need to make additional assumptions of ergodicity or metric transitivity; the theory proceeds entirely by inference from macroscopic measurements and the underlying dynamical assumptions. Moreover, the method of maximizing the entropy is completely general and applies, in particular, to irreversible processes as well as to reversible ones. The next three chapters provide a broader framework - at once Bayesian and objective - for maximum entropy inference. The basic principles of inference, including the usual axioms of probability, are seen to rest on nothing more than requirements of consistency, above all, the requirement that in two problems where we have the same information we must assign the same probabilities. Thus, statistical mechanics is viewed as a branch of a general theory of inference, and the latter as an extension of the ordinary logic of consistency. Those who are familiar with the literature of statistics and statistical mechanics will recognize in both of these steps a genuine 'scientific revolution' - a complete reversal of earlier conceptions - and one of no small significance.