Nelson Mathematics for Cambridge International A Level: Probability and Statistics 1 PDF Download

Author: Janet Crawshaw
Publisher: Oxford University Press - Children
ISBN: 019837982X
Category : Mathematics
Languages : en
Pages : 244

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Book Description
The Nelson Mathematics for Cambridge International AS & A Level series is tailored to the needs of A & AS level students of the latest 9709 syllabus. Developed by a team of experienced examiners and international authors, it provides comprehensive coverage for this syllabus and effective preparation for the Cambridge exams. Nelson Probability and Statistics 1 for Cambridge International A Level is for students taking the S1 exam paper. The text provides introductions to topics and step-by-step worked examples to aid students in their understanding of the course material. Mixed exercises with more detailed questions, similar to those found in the actual examinations, test the knowledge of content covered in previous chapters, helping students to apply knowledge. In addition, practice exam papers provide students with opportunities for effective exam preparation and so help them reach their full potential.

Author: Sophie Goldie
Publisher: Hachette UK
ISBN: 1510421033
Category : Study Aids
Languages : en
Pages : 228

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Book Description
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 5 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 Boost eBook.* *To have full access to the eBook and Integral resources you must be subscribed to both Boost and Integral. To trial our eBooks and/or subscribe to Boost, visit: www.hoddereducation.com/Boost; 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 Probability and Statistics 1, including representation of data, permutations and combinations, probability, discrete random variables and the normal distribution.

Author: Roman Vershynin
Publisher: Cambridge University Press
ISBN: 1108415199
Category : Business & Economics
Languages : en
Pages : 299

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Book Description
An integrated package of powerful probabilistic tools and key applications in modern mathematical data science.

Author: Janet Crawshaw
Publisher: Oxford University Press - Children
ISBN: 0198379854
Category : Mathematics
Languages : en
Pages : 228

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Book Description
The Nelson Mathematics for Cambridge International AS & A Level series is tailored to the needs of A and AS level students of the latest 9709 syllabus. Developed by a team of experienced examiners and international authors, it provides comprehensive coverage for this syllabus and effective preparation for the Cambridge exams. Nelson Probability and Statistics 2 for Cambridge International A Level is for students taking the S2 exam paper. The text aids students in their understanding of course material by providing introductions to concepts accompanied by example questions and their solutions, showing each step of the workings and commenting on the reasoning processes involved. Mixed exercises with more detailed questions, similar to those found in the actual examinations, test the knowledge of content covered in previous chapters, helping students to apply knowledge. In addition, practice exam papers provide students with opportunities for effective exam preparation and so help them reach their full

Author: Kandethody M. Ramachandran
Publisher: Elsevier
ISBN: 012417132X
Category : Mathematics
Languages : en
Pages : 825

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Book Description
Mathematical Statistics with Applications in R, Second Edition, offers a modern calculus-based theoretical introduction to mathematical statistics and applications. The book covers many modern statistical computational and simulation concepts that are not covered in other texts, such as the Jackknife, bootstrap methods, the EM algorithms, and Markov chain Monte Carlo (MCMC) methods such as the Metropolis algorithm, Metropolis-Hastings algorithm and the Gibbs sampler. By combining the discussion on the theory of statistics with a wealth of real-world applications, the book helps students to approach statistical problem solving in a logical manner.This book provides a step-by-step procedure to solve real problems, making the topic more accessible. It includes goodness of fit methods to identify the probability distribution that characterizes the probabilistic behavior or a given set of data. Exercises as well as practical, real-world chapter projects are included, and each chapter has an optional section on using Minitab, SPSS and SAS commands. The text also boasts a wide array of coverage of ANOVA, nonparametric, MCMC, Bayesian and empirical methods; solutions to selected problems; data sets; and an image bank for students.Advanced undergraduate and graduate students taking a one or two semester mathematical statistics course will find this book extremely useful in their studies. - Step-by-step procedure to solve real problems, making the topic more accessible - Exercises blend theory and modern applications - Practical, real-world chapter projects - Provides an optional section in each chapter on using Minitab, SPSS and SAS commands - Wide array of coverage of ANOVA, Nonparametric, MCMC, Bayesian and empirical methods

Author: Andrew Gelman
Publisher: Cambridge University Press
ISBN: 110702398X
Category : Business & Economics
Languages : en
Pages : 551

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Book Description
A practical approach to using regression and computation to solve real-world problems of estimation, prediction, and causal inference.

Author: Janet Crawshaw
Publisher: Oxford University Press, USA
ISBN: 9781408515624
Category : Juvenile Nonfiction
Languages : en
Pages : 0

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Book Description
Tailored to the needs of A & AS level students of the latest 9709 syllabus, this series has been developed by experienced examiners and international authors to provide comprehensive and effective preparation for this syllabus and the Cambridge exams.

Author: Matthew A. Carlton
Publisher: Springer
ISBN: 3319524011
Category : Mathematics
Languages : en
Pages : 664

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Book Description
This updated and revised first-course textbook in applied probability provides a contemporary and lively post-calculus introduction to the subject of probability. The exposition reflects a desirable balance between fundamental theory and many applications involving a broad range of real problem scenarios. It is intended to appeal to a wide audience, including mathematics and statistics majors, prospective engineers and scientists, and those business and social science majors interested in the quantitative aspects of their disciplines. The textbook contains enough material for a year-long course, though many instructors will use it for a single term (one semester or one quarter). As such, three course syllabi with expanded course outlines are now available for download on the book’s page on the Springer website. A one-term course would cover material in the core chapters (1-4), supplemented by selections from one or more of the remaining chapters on statistical inference (Ch. 5), Markov chains (Ch. 6), stochastic processes (Ch. 7), and signal processing (Ch. 8—available exclusively online and specifically designed for electrical and computer engineers, making the book suitable for a one-term class on random signals and noise). For a year-long course, core chapters (1-4) are accessible to those who have taken a year of univariate differential and integral calculus; matrix algebra, multivariate calculus, and engineering mathematics are needed for the latter, more advanced chapters. At the heart of the textbook’s pedagogy are 1,100 applied exercises, ranging from straightforward to reasonably challenging, roughly 700 exercises in the first four “core” chapters alone—a self-contained textbook of problems introducing basic theoretical knowledge necessary for solving problems and illustrating how to solve the problems at hand – in R and MATLAB, including code so that students can create simulations. New to this edition • Updated and re-worked Recommended Coverage for instructors, detailing which courses should use the textbook and how to utilize different sections for various objectives and time constraints • Extended and revised instructions and solutions to problem sets • Overhaul of Section 7.7 on continuous-time Markov chains • Supplementary materials include three sample syllabi and updated solutions manuals for both instructors and students

Author: Ilke Demir
Publisher: Springer Nature
ISBN: 3030798917
Category : Mathematics
Languages : en
Pages : 374

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Book Description
This volume highlights recent advances in data science, including image processing and enhancement on large data, shape analysis and geometry processing in 2D/3D, exploration and understanding of neural networks, and extensions to atypical data types such as social and biological signals. The contributions are based on discussions from two workshops under Association for Women in Mathematics (AWM), namely the second Women in Data Science and Mathematics (WiSDM) Research Collaboration Workshop that took place between July 29 and August 2, 2019 at the Institute for Computational and Experimental Research in Mathematics (ICERM) in Providence, Rhode Island, and the third Women in Shape (WiSh) Research Collaboration Workshop that took place between July 16 and 20, 2018 at Trier University in Robert-Schuman-Haus, Trier, Germany. These submissions, seeded by working groups at the conference, form a valuable source for readers who are interested in ideas and methods developed in interdisciplinary research fields. The book features ideas, methods, and tools developed through a broad range of domains, ranging from theoretical analysis on graph neural networks to applications in health science. It also presents original results tackling real-world problems that often involve complex data analysis on large multi-modal data sources.

Author: Fred L. Bookstein
Publisher: Cambridge University Press
ISBN: 1108126065
Category : Medical
Languages : en
Pages : 547

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Book Description
This book builds a much-needed bridge between biostatistics and organismal biology by linking the arithmetic of statistical studies of organismal form to the biological inferences that may follow from it. It incorporates a cascade of new explanations of regression, correlation, covariance analysis, and principal components analysis, before applying these techniques to an increasingly common data resource: the description of organismal forms by sets of landmark point configurations. For each data set, multiple analyses are interpreted and compared for insight into the relation between the arithmetic of the measurements and the rhetoric of the subsequent biological explanations. The text includes examples that range broadly over growth, evolution, and disease. For graduate students and researchers alike, this book offers a unique consideration of the scientific context surrounding the analysis of form in today's biosciences.