Rising Stars Mathematics Year 1 Practice Book Pack (single Copies of B
Author: Hodder Education Group
Publisher:
Published: 2015-12-04
Total Pages:
ISBN-13: 9781783399031
DOWNLOAD EBOOKRead and Download eBook Full
Author: Hodder Education Group
Publisher:
Published: 2015-12-04
Total Pages:
ISBN-13: 9781783399031
DOWNLOAD EBOOKAuthor: Paul Broadbent
Publisher:
Published: 2015-12-25
Total Pages: 64
ISBN-13: 9781783398119
DOWNLOAD EBOOKRegular practice is essential to achieving mastery. The write-in Year 1 Practice Book B provides carefully structured practice, including variation, for all concepts in the Textbooks. They help children to embed and consolidate their conceptual understanding and dig deeper into concepts through intelligent practice. To be used with the Rising Stars Mathematics Textbook with further practice books available; Rising Stars Mathematics Year 1 Practice Book A 9781783398102 and Rising Stars Mathematics Year 1 Practice Book C 9781783398126.
Author: Paul Broadbent
Publisher:
Published: 2015-12-25
Total Pages: 56
ISBN-13: 9781783398102
DOWNLOAD EBOOKProvide careful and structured practice in maths mastery for children at home or school, covering all concepts that would be covered in class. -Embed and consolidate conceptual understanding. -Dig deeper into mathematical concepts through intelligent practice. -Provide structure and clarity with a write in, levelled book.
Author: Paul Broadbent
Publisher:
Published: 2015-12-25
Total Pages: 56
ISBN-13: 9781783398126
DOWNLOAD EBOOKRegular practice is essential to achieving mastery. The write-in Year 1 Practice Book C provides carefully structured practice, including variation, for all concepts in the Textbooks. They help children to embed and consolidate their conceptual understanding and dig deeper into concepts through intelligent practice. To be used with the Rising Stars Mathematics Textbook with further practice books available; Rising Stars Mathematics Year 1 Practice Book A 9781783398102 and Rising Stars Mathematics Year 1 Practice Book B 9781783398119.
Author: Joseph K. Blitzstein
Publisher: CRC Press
Published: 2014-07-24
Total Pages: 599
ISBN-13: 1466575573
DOWNLOAD EBOOKDeveloped from celebrated Harvard statistics lectures, Introduction to Probability provides essential language and tools for understanding statistics, randomness, and uncertainty. The book explores a wide variety of applications and examples, ranging from coincidences and paradoxes to Google PageRank and Markov chain Monte Carlo (MCMC). Additional application areas explored include genetics, medicine, computer science, and information theory. The print book version includes a code that provides free access to an eBook version. The authors present the material in an accessible style and motivate concepts using real-world examples. Throughout, they use stories to uncover connections between the fundamental distributions in statistics and conditioning to reduce complicated problems to manageable pieces. The book includes many intuitive explanations, diagrams, and practice problems. Each chapter ends with a section showing how to perform relevant simulations and calculations in R, a free statistical software environment.
Author: Althea A. Foster
Publisher: Longman
Published: 2007
Total Pages:
ISBN-13: 9781405862813
DOWNLOAD EBOOKAuthor: Lynn Harold Loomis
Publisher: World Scientific Publishing Company
Published: 2014-02-26
Total Pages: 595
ISBN-13: 9814583952
DOWNLOAD EBOOKAn authorised reissue of the long out of print classic textbook, Advanced Calculus by the late Dr Lynn Loomis and Dr Shlomo Sternberg both of Harvard University has been a revered but hard to find textbook for the advanced calculus course for decades.This book is based on an honors course in advanced calculus that the authors gave in the 1960's. The foundational material, presented in the unstarred sections of Chapters 1 through 11, was normally covered, but different applications of this basic material were stressed from year to year, and the book therefore contains more material than was covered in any one year. It can accordingly be used (with omissions) as a text for a year's course in advanced calculus, or as a text for a three-semester introduction to analysis.The prerequisites are a good grounding in the calculus of one variable from a mathematically rigorous point of view, together with some acquaintance with linear algebra. The reader should be familiar with limit and continuity type arguments and have a certain amount of mathematical sophistication. As possible introductory texts, we mention Differential and Integral Calculus by R Courant, Calculus by T Apostol, Calculus by M Spivak, and Pure Mathematics by G Hardy. The reader should also have some experience with partial derivatives.In overall plan the book divides roughly into a first half which develops the calculus (principally the differential calculus) in the setting of normed vector spaces, and a second half which deals with the calculus of differentiable manifolds.
Author: David Lippman
Publisher:
Published: 2012-09-07
Total Pages: 0
ISBN-13: 9781479276530
DOWNLOAD EBOOKMath in Society is a survey of contemporary mathematical topics, appropriate for a college-level topics course for liberal arts major, or as a general quantitative reasoning course.This book is an open textbook; it can be read free online at http://www.opentextbookstore.com/mathinsociety/. Editable versions of the chapters are available as well.
Author: Marc Peter Deisenroth
Publisher: Cambridge University Press
Published: 2020-04-23
Total Pages: 392
ISBN-13: 1108569323
DOWNLOAD EBOOKThe fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics. These topics are traditionally taught in disparate courses, making it hard for data science or computer science students, or professionals, to efficiently learn the mathematics. This self-contained textbook bridges the gap between mathematical and machine learning texts, introducing the mathematical concepts with a minimum of prerequisites. It uses these concepts to derive four central machine learning methods: linear regression, principal component analysis, Gaussian mixture models and support vector machines. For students and others with a mathematical background, these derivations provide a starting point to machine learning texts. For those learning the mathematics for the first time, the methods help build intuition and practical experience with applying mathematical concepts. Every chapter includes worked examples and exercises to test understanding. Programming tutorials are offered on the book's web site.
Author: Gary Haggard
Publisher: Cengage Learning
Published: 2006
Total Pages: 0
ISBN-13: 9780534495015
DOWNLOAD EBOOKMaster the fundamentals of discrete mathematics with DISCRETE MATHEMATICS FOR COMPUTER SCIENCE with Student Solutions Manual CD-ROM! An increasing number of computer scientists from diverse areas are using discrete mathematical structures to explain concepts and problems and this mathematics text shows you how to express precise ideas in clear mathematical language. Through a wealth of exercises and examples, you will learn how mastering discrete mathematics will help you develop important reasoning skills that will continue to be useful throughout your career.