A Guide To Mathematics R 187
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Asian Research in Mathematics Education
Author | : Bill Atweh |
Publisher | : Springer Nature |
Total Pages | : 187 |
Release | : 2023-05-17 |
Genre | : Education |
ISBN | : 9819906431 |
This book focuses on the development of research in mathematics education cultures and its products from the perspective of local educators. It consists of contributions from Mainland China, Indonesia, Korea, Macao, Singapore, the Philippines, and Turkey. This book examines the development of the culture of research in the respective countries and also reviews the research conducted in the recent past in mathematics education. It takes a critical stance through identifying the various accomplishments, and identifying challenges for the future of research in terms of its diversification and quality. Divided into two sections, the first section considers factors around the development of a research culture in the respective countries by focusing on the means used to develop research expertise and quality. The second section consists of overviews of the area of research and methodologies conducted in mathematics education in the various countries, with the intention of highlighting the research topics conducted as well as discussing omissions of such research.
Book of Proof
Author | : Richard H. Hammack |
Publisher | : |
Total Pages | : 314 |
Release | : 2016-01-01 |
Genre | : Mathematics |
ISBN | : 9780989472111 |
This book is an introduction to the language and standard proof methods of mathematics. It is a bridge from the computational courses (such as calculus or differential equations) that students typically encounter in their first year of college to a more abstract outlook. It lays a foundation for more theoretical courses such as topology, analysis and abstract algebra. Although it may be more meaningful to the student who has had some calculus, there is really no prerequisite other than a measure of mathematical maturity.
Meeting the Standards in Primary Mathematics
Author | : Tony Brown |
Publisher | : Taylor & Francis |
Total Pages | : 257 |
Release | : 2003-09-02 |
Genre | : Education |
ISBN | : 1134533160 |
Written in response to the new ITT NC requirements for student teachers Comprehensive guide covering all aspects of primary teacher training relating to mathematics and the Standards required to reach qualified teacher status A strong and adoptable series for all ITT courses Informs teachers of exactly what they need to know to teach the subject and provides further information in continuing professional development issues There is increasing pressure on student teachers to develop their subject classroom competence in a short space of time - this should help relieve the burden Part of the successful Meeting the Standards Series which students on BEd and PGCE courses and teachers will already be familiar with Includes a chapter dealing with the transition from teacher training to being a Newly Qualified Teacher.
The H-Function
Author | : A.M. Mathai |
Publisher | : Springer Science & Business Media |
Total Pages | : 276 |
Release | : 2009-10-10 |
Genre | : Science |
ISBN | : 1441909168 |
TheH-function or popularly known in the literature as Fox’sH-function has recently found applications in a large variety of problems connected with reaction, diffusion, reaction–diffusion, engineering and communication, fractional differ- tial and integral equations, many areas of theoretical physics, statistical distribution theory, etc. One of the standard books and most cited book on the topic is the 1978 book of Mathai and Saxena. Since then, the subject has grown a lot, mainly in the elds of applications. Due to popular demand, the authors were requested to - grade and bring out a revised edition of the 1978 book. It was decided to bring out a new book, mostly dealing with recent applications in statistical distributions, pa- way models, nonextensive statistical mechanics, astrophysics problems, fractional calculus, etc. and to make use of the expertise of Hans J. Haubold in astrophysics area also. It was decided to con ne the discussion toH-function of one scalar variable only. Matrix variable cases and many variable cases are not discussed in detail, but an insight into these areas is given. When going from one variable to many variables, there is nothing called a unique bivariate or multivariate analogue of a givenfunction. Whatever be the criteria used, there may be manydifferentfunctions quali ed to be bivariate or multivariate analogues of a given univariate function. Some of the bivariate and multivariateH-functions, currently in the literature, are also questioned by many authors.
Coding the Matrix
Author | : Philip N. Klein |
Publisher | : |
Total Pages | : 530 |
Release | : 2013-07 |
Genre | : Algebras, Linear |
ISBN | : 9780615856735 |
An engaging introduction to vectors and matrices and the algorithms that operate on them, intended for the student who knows how to program. Mathematical concepts and computational problems are motivated by applications in computer science. The reader learns by "doing," writing programs to implement the mathematical concepts and using them to carry out tasks and explore the applications. Examples include: error-correcting codes, transformations in graphics, face detection, encryption and secret-sharing, integer factoring, removing perspective from an image, PageRank (Google's ranking algorithm), and cancer detection from cell features. A companion web site, codingthematrix.com provides data and support code. Most of the assignments can be auto-graded online. Over two hundred illustrations, including a selection of relevant "xkcd" comics. Chapters: "The Function," "The Field," "The Vector," "The Vector Space," "The Matrix," "The Basis," "Dimension," "Gaussian Elimination," "The Inner Product," "Special Bases," "The Singular Value Decomposition," "The Eigenvector," "The Linear Program" A new edition of this text, incorporating corrections and an expanded index, has been issued as of September 4, 2013, and will soon be available on Amazon.
Mathematics for Machine Learning
Author | : Marc Peter Deisenroth |
Publisher | : Cambridge University Press |
Total Pages | : 392 |
Release | : 2020-04-23 |
Genre | : Computers |
ISBN | : 1108569323 |
The 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.
The Basic Guide to Research Sources
Author | : Joanne Soderman |
Publisher | : Scarborough, Ont. : New American Library of Canada |
Total Pages | : 266 |
Release | : 1975 |
Genre | : Reference |
ISBN | : |
The Book of R
Author | : Tilman M. Davies |
Publisher | : No Starch Press |
Total Pages | : 833 |
Release | : 2016-07-16 |
Genre | : Computers |
ISBN | : 1593276516 |
The Book of R is a comprehensive, beginner-friendly guide to R, the world’s most popular programming language for statistical analysis. Even if you have no programming experience and little more than a grounding in the basics of mathematics, you’ll find everything you need to begin using R effectively for statistical analysis. You’ll start with the basics, like how to handle data and write simple programs, before moving on to more advanced topics, like producing statistical summaries of your data and performing statistical tests and modeling. You’ll even learn how to create impressive data visualizations with R’s basic graphics tools and contributed packages, like ggplot2 and ggvis, as well as interactive 3D visualizations using the rgl package. Dozens of hands-on exercises (with downloadable solutions) take you from theory to practice, as you learn: –The fundamentals of programming in R, including how to write data frames, create functions, and use variables, statements, and loops –Statistical concepts like exploratory data analysis, probabilities, hypothesis tests, and regression modeling, and how to execute them in R –How to access R’s thousands of functions, libraries, and data sets –How to draw valid and useful conclusions from your data –How to create publication-quality graphics of your results Combining detailed explanations with real-world examples and exercises, this book will provide you with a solid understanding of both statistics and the depth of R’s functionality. Make The Book of R your doorway into the growing world of data analysis.
The R Book
Author | : Michael J. Crawley |
Publisher | : John Wiley & Sons |
Total Pages | : 953 |
Release | : 2007-06-13 |
Genre | : Mathematics |
ISBN | : 9780470515068 |
The high-level language of R is recognized as one of the mostpowerful and flexible statistical software environments, and israpidly becoming the standard setting for quantitative analysis,statistics and graphics. R provides free access to unrivalledcoverage and cutting-edge applications, enabling the user to applynumerous statistical methods ranging from simple regression to timeseries or multivariate analysis. Building on the success of the author’s bestsellingStatistics: An Introduction using R, The R Book ispacked with worked examples, providing an all inclusive guide to R,ideal for novice and more accomplished users alike. The bookassumes no background in statistics or computing and introduces theadvantages of the R environment, detailing its applications in awide range of disciplines. Provides the first comprehensive reference manual for the Rlanguage, including practical guidance and full coverage of thegraphics facilities. Introduces all the statistical models covered by R, beginningwith simple classical tests such as chi-square and t-test. Proceeds to examine more advance methods, from regression andanalysis of variance, through to generalized linear models,generalized mixed models, time series, spatial statistics,multivariate statistics and much more. The R Book is aimed at undergraduates, postgraduates andprofessionals in science, engineering and medicine. It is alsoideal for students and professionals in statistics, economics,geography and the social sciences.