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Thursday, February 28, 2019

Books for understanding mathematics and Statistics | Books - Cambridge University Press

Check out these books below by Cambridge University Press.  

Photo: Pexels

Abstract Algebra with Applications

Abstract Algebra with Applications
Abstract Algebra with Applications provides a friendly and concise introduction to algebra, with an emphasis on its uses in the modern world. The first part of this book covers groups, after some preliminaries on sets, functions, relations, and induction, and features applications such as public-key cryptography, Sudoku, the finite Fourier transform, and symmetry in chemistry and physics. The second part of this book covers rings and fields, and features applications such as random number generators, error correcting codes, the Google page rank algorithm, communication networks, and elliptic curve cryptography...

Intended for a year-long undergraduate course in algebra for mathematics, engineering, and computer science majors, the only prerequisites are calculus and a bit of courage when asked to do a short proof.
  • Includes interesting computational examples where students can use their preferred software, including Mathematica, Scientific Workplace and Group Explorer
  • Connects theory with practice by featuring plenty of examples and applications
  • Emphasizes finite fields and rings and the ways in which the finite mirrors the infinite, making the subject accessible to students
Read more...  

Modern Statistics for Modern Biology 

Modern Statistics for Modern Biology
If you are a biologist and want to get the best out of the powerful methods of modern computational statistics, this is your book. You can visualize and analyze your own data, apply unsupervised and supervised learning, integrate datasets, apply hypothesis testing, and make publication-quality figures using the power of R/Bioconductor and ggplot2. This book will teach you 'cooking from scratch', from raw data to beautiful illuminating output, as you learn to write your own scripts in the R language and to use advanced statistics packages from CRAN and Bioconductor...

Using a minimum of mathematical notation, it builds understanding from well-chosen examples, simulation, visualization, and above all hands-on interaction with data and code.
  • Introduces methods on a 'need to know' basis, so students tackle biological questions immediately and understand motivation for the methods
  • Contains real-life examples done from scratch, guiding students through realistic complexities and building practical intuition
  • Includes a wrap-up chapter that explains the complete workflow from design of experiments to analysis of results, identifying common pitfalls with big data

Linear Algebra 

Linear Algebra
Linear Algebra offers a unified treatment of both matrix-oriented and theoretical approaches to the course, which will be useful for classes with a mix of mathematics, physics, engineering, and computer science students...
  • Introduces central topics, such as vector spaces, linear maps, linear dependence and eigenvalues early in the book with the aim of helping students transition from calculus to rigorous mathematics
  • Motivates the reader whilst introducing new topics, definitions, and appropriate examples in connection with the core concepts presented early in the text so that students will be able to go back to these vital notions and, by the time the course ends, will have worked with them extensively
  • Includes many pedagogical features, such as: 'Quick Exercises' throughout with answers upside-down at the bottom of the page; periodic 'Perspectives' that collect various viewpoints on particular topics developed throughout the text; and numerous in-text examples, end-of-chapter exercises, and hints and answers to selected problems at the end of the book

Enjoy the Read! 

Source: Cambridge University Press