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Dealing with mechanics and the solving of mechanical problems with the help of pure mathematics, this A-Level text introduces at an early stage an appreciation of the properties of vectors. Throughout the book problems are solved using vector methods where appropriate, and many worked examples are provided to illustrate each main development of a topic. A set of straightforward problems follows each section, and a selection of more challenging questions appears in the miscellaneous exercises at the end of most chapters, with multiple-choice questions on most topics.
This volume continues the work covered in Core Maths or Mathematics - The Core Course for Advanced Level to provide a full two-year course in Pure Mathematics for A-Level.
Sinai's book leads the student through the standard material for ProbabilityTheory, with stops along the way for interesting topics such as statistical mechanics, not usually included in a book for beginners. The first part of the book covers discrete random variables, using the same approach, basedon Kolmogorov's axioms for probability, used later for the general case. The text is divided into sixteen lectures, each covering a major topic. The introductory notions and classical results are included, of course: random variables, the central limit theorem, the law of large numbers, conditional probability, random walks, etc. Sinai's style is accessible and clear, with interesting examples to accompany new ideas. Besides statistical mechanics, other interesting, less common topics found in the book are: percolation, the concept of stability in the central limit theorem and the study of probability of large deviations. Little more than a standard undergraduate course in analysis is assumed of the reader. Notions from measure theory and Lebesgue integration are introduced in the second half of the text. The book is suitable for second or third year students in mathematics, physics or other natural sciences. It could also be usedby more advanced readers who want to learn the mathematics of probability theory and some of its applications in statistical physics.
Exam board: Cambridge Assessment International Education Level: A-level Subject: Mathematics First teaching: September 2018 First exams: Summer 2020 Endorsed by Cambridge Assessment International Education to provide full support for Paper 4 of the syllabus for examination from 2020. Take mathematical understanding to the next level with this accessible series, written by experienced authors, examiners and teachers. - Improve confidence as a mathematician with clear explanations, worked examples, diverse activities and engaging discussion points. - Advance problem-solving, interpretation and communication skills through a wealth of questions that promote higher-order thinking. - Prepare for further study or life beyond the classroom by applying mathematics to other subjects and modelling real-world situations. - Reinforce learning with opportunities for digital practice via links to the Mathematics in Education and Industry's (MEI) Integral platform in the eTextbooks.* *To have full access to the eTextbooks and Integral resources you must be subscribed to both Dynamic Learning and Integral. To trial our eTextbooks and/or subscribe to Dynamic Learning, visit: www.hoddereducation.co.uk/dynamic-learning; to view samples of the Integral resources and/or subscribe to Integral, visit integralmaths.org/international Please note that the Integral resources have not been through the Cambridge International endorsement process. This book covers the syllabus content for Further Probability and Statistics, including continuous random variables, inference using normal and t-distributions, chi-squared tests, non-parametric tests and probability generating functions. About the series: Four separate textbooks ensure full coverage of the latest Cambridge International AS & A Level Further Mathematics syllabus (9231). Student and Whiteboard eTextbook editions are also available. Further Pure Mathematics 1: Student Textbook (ISBN 9781510421783), Student eTextbook (ISBN 9781510422025), Whiteboard eTextbook (ISBN 9781510422032) Further Pure Mathematics 2: Student Textbook (ISBN 9781510421790), Student eTextbook (ISBN 9781510422063), Whiteboard eTextbook (ISBN 9781510422070) Further Mechanics: Student Textbook (ISBN 9781510421806), Student eTextbook (ISBN 9781510422100), Whiteboard eTextbook (ISBN 9781510422117) Further Probability & Statistics: Student Textbook (ISBN 9781510421813), Student eTextbook (ISBN 9781510422148), Whiteboard eTextbook (ISBN 9781510422155)
The ideas of probability are all around us. Lotteries, casino gambling, the al most non-stop polling which seems to mold public policy more and more these are a few of the areas where principles of probability impinge in a direct way on the lives and fortunes of the general public. At a more re moved level there is modern science which uses probability and its offshoots like statistics and the theory of random processes to build mathematical descriptions of the real world. In fact, twentieth-century physics, in embrac ing quantum mechanics, has a world view that is at its core probabilistic in nature, contrary to the deterministic one of classical physics. In addition to all this muscular evidence of the importance of probability ideas it should also be said that probability can be lots of fun. It is a subject where you can start thinking about amusing, interesting, and often difficult problems with very little mathematical background. In this book, I wanted to introduce a reader with at least a fairly decent mathematical background in elementary algebra to this world of probabil ity, to the way of thinking typical of probability, and the kinds of problems to which probability can be applied. I have used examples from a wide variety of fields to motivate the discussion of concepts.
This classroom-tested textbook is an introduction to probability theory, with the right balance between mathematical precision, probabilistic intuition, and concrete applications. Introduction to Probability covers the material precisely, while avoiding excessive technical details. After introducing the basic vocabulary of randomness, including events, probabilities, and random variables, the text offers the reader a first glimpse of the major theorems of the subject: the law of large numbers and the central limit theorem. The important probability distributions are introduced organically as they arise from applications. The discrete and continuous sides of probability are treated together to emphasize their similarities. Intended for students with a calculus background, the text teaches not only the nuts and bolts of probability theory and how to solve specific problems, but also why the methods of solution work.
Cambridge International AS & A Level Further Mathematics supports students following the 9231 syllabus. This single coursebook comprehensively covers all four modules of the syllabus and helps support students in their studies and develops their mathematical skills. Authored by experienced teachers of Further Mathematics, the coursebook provides detailed explanations and clear worked examples with practice exercises and exam-style questions. Answers are at the back of the book.
This volume is a collection of lecture notes for six of the ten courses given in Buzios, Brazil by prominent probabilists at the 2010 Clay Mathematics Institute Summer School, ``Probability and Statistical Physics in Two and More Dimensions'' and at the XIV Brazilian School of Probability. In the past ten to fifteen years, various areas of probability theory related to statistical physics, disordered systems and combinatorics have undergone intensive development. A number of these developments deal with two-dimensional random structures at their critical points, and provide new tools and ways of coping with at least some of the limitations of Conformal Field Theory that had been so successfully developed in the theoretical physics community to understand phase transitions of two-dimensional systems. Included in this selection are detailed accounts of all three foundational courses presented at the Clay school--Schramm-Loewner Evolution and other Conformally Invariant Objects, Noise Sensitivity and Percolation, Scaling Limits of Random Trees and Planar Maps--together with contributions on Fractal and Multifractal properties of SLE and Conformal Invariance of Lattice Models. Finally, the volume concludes with extended articles based on the courses on Random Polymers and Self-Avoiding Walks given at the Brazilian School of Probability during the final week of the school. Together, these notes provide a panoramic, state-of-the-art view of probability theory areas related to statistical physics, disordered systems and combinatorics. Like the lectures themselves, they are oriented towards advanced students and postdocs, but experts should also find much of interest.