A History of Mathematical Notations

A History of Mathematical Notations PDF Author: Florian Cajori
Publisher: Courier Corporation
ISBN: 0486161161
Category : Mathematics
Languages : en
Pages : 865

Book Description
This classic study notes the origin of a mathematical symbol, the competition it encountered, its spread among writers in different countries, its rise to popularity, and its eventual decline or ultimate survival. 1929 edition.

Comprehensive List of Mathematical Symbols

Comprehensive List of Mathematical Symbols PDF Author: Math Vault
Publisher: Math Vault Publishing
ISBN:
Category : Mathematics
Languages : en
Pages : 76

Book Description
Ever wonder if there's a reference guide out there summarizing most of the symbols used in mathematics, along with contextual examples and LaTeX code so that you can pick up the various topics of mathematics at an unusual speed? Well now there is! In this jam-packed 75-page eBook, the Comprehensive List of Mathematical Symbols will take you through thousands of symbols in 10+ topics and 6 main categories. Each symbol also comes with their own defining examples, LaTeX codes and links to additional resources, making the eBook both a handy reference and a powerful tool for consolidating one's foundation of mathematics. Highlights - Featuring 1000+ of symbols from basic math, algebra, logic, set theory to calculus, analysis, probability and statistics - Comes with LaTeX code, defining contextual examples and links to additional resources - Clear. Concise. Straight-to-the-point with no fluff. - Informative. Engaging. Excellent for shortening the learning/reviewing curve. Table of Contents 1) Constants Key Mathematical Numbers Key Mathematical Sets Key Mathematical Infinities Other Key Mathematical Objects 2) Variables Variables for Numbers Variables in Geometry Variables in Logic Variables in Set Theory Variables in Linear/Abstract Algebra Variables in Probability and Statistics Variables in Calculus 3) Delimiters Common Delimiters Other Delimiters 4) Alphabet Letters Greek Letters Used in Mathematics Other Greek Letters 5) Operators Common Operators Number-related Operators Common Number-based Operators Complex-number-based Operators Function-related Operators Common Function-based Operators Elementary Functions Key Calculus-related Functions and Transforms Other Key Functions Operators in Geometry Operators in Logic Logical Connectives Quantifiers Substitution/Valuation-based Operators Set-related Operators Operators in Algebra Vector-related Operators Matrix-related Operators Vector-space-related Operators Abstract-algebra-related Operators Operators in Probability and Statistics Combinatorial Operators Probability-related Operators Probability-related Functions Discrete Probability Distributions Continuous Probability Distributions and Associated Functions Statistical Operators Operators in Calculus Operators Related to Sequence, Series and Limit Derivative-based Operators Integral-based Operators 6) Relational Symbols Equality-based Relational Symbols Comparison-based Relational Symbols Number-related Relational Symbols Relational Symbols in Geometry Relational Symbols in Logic Set-related Relational Symbols Relational Symbols in Abstract Algebra Relational Symbols in Probability and Statistics Relational Symbols in Calculus 7) Notational Symbols Common Notational Symbols Intervals Notational Symbols in Geometry and Trigonometry Notational Symbols in Probability and Statistics Notational Symbols in Calculus

Principia Mathematica

Principia Mathematica PDF Author: Alfred North Whitehead
Publisher:
ISBN:
Category : Logic, Symbolic and mathematical
Languages : en
Pages : 688

Book Description

Mathematical Notation

Mathematical Notation PDF Author: Edward Scheinerman
Publisher: Edward Scheinerman
ISBN: 1466230525
Category : Mathematics
Languages : en
Pages : 92

Book Description
Mathematics is a language with a unique vocabulary, written with a dizzying array of often incomprehensible symbols. If we are unsure of the meaning or usage of a mathematical word, a quick internet search is invaluable. But what are we to do when confronted with some strange mathematical hieroglyph? What does one type into the search bar? This book is the answer! Our goal is to cover mathematical notation commonly used by engineers and scientists---notation a university student is likely to encounter. We make no attempt to teach the mathematics behind these symbols. Rather, our goal is to give reminders of what these symbols mean; from there, we can consult textbooks or resources on the web. The book is organized by mathematical topic, but multiple indices steer the reader to each symbol's explanation. We also show how to produce the symbols in LaTeX and give guidance on their mathematical usage.

Math with Bad Drawings

Math with Bad Drawings PDF Author: Ben Orlin
Publisher: Black Dog & Leventhal
ISBN: 0316509027
Category : Mathematics
Languages : en
Pages : 556

Book Description
A hilarious reeducation in mathematics-full of joy, jokes, and stick figures-that sheds light on the countless practical and wonderful ways that math structures and shapes our world. In Math With Bad Drawings, Ben Orlin reveals to us what math actually is; its myriad uses, its strange symbols, and the wild leaps of logic and faith that define the usually impenetrable work of the mathematician. Truth and knowledge come in multiple forms: colorful drawings, encouraging jokes, and the stories and insights of an empathetic teacher who believes that math should belong to everyone. Orlin shows us how to think like a mathematician by teaching us a brand-new game of tic-tac-toe, how to understand an economic crises by rolling a pair of dice, and the mathematical headache that ensues when attempting to build a spherical Death Star. Every discussion in the book is illustrated with Orlin's trademark "bad drawings," which convey his message and insights with perfect pitch and clarity. With 24 chapters covering topics from the electoral college to human genetics to the reasons not to trust statistics, Math with Bad Drawings is a life-changing book for the math-estranged and math-enamored alike.

Discrete Mathematics

Discrete Mathematics PDF Author: Oscar Levin
Publisher: Createspace Independent Publishing Platform
ISBN: 9781534970748
Category :
Languages : en
Pages : 342

Book Description
This gentle introduction to discrete mathematics is written for first and second year math majors, especially those who intend to teach. The text began as a set of lecture notes for the discrete mathematics course at the University of Northern Colorado. This course serves both as an introduction to topics in discrete math and as the "introduction to proof" course for math majors. The course is usually taught with a large amount of student inquiry, and this text is written to help facilitate this. Four main topics are covered: counting, sequences, logic, and graph theory. Along the way proofs are introduced, including proofs by contradiction, proofs by induction, and combinatorial proofs. The book contains over 360 exercises, including 230 with solutions and 130 more involved problems suitable for homework. There are also Investigate! activities throughout the text to support active, inquiry based learning. While there are many fine discrete math textbooks available, this text has the following advantages: It is written to be used in an inquiry rich course. It is written to be used in a course for future math teachers. It is open source, with low cost print editions and free electronic editions.

Mathematical Writing

Mathematical Writing PDF Author: Franco Vivaldi
Publisher: Springer
ISBN: 1447165276
Category : Mathematics
Languages : en
Pages : 213

Book Description
This book teaches the art of writing mathematics, an essential -and difficult- skill for any mathematics student. The book begins with an informal introduction on basic writing principles and a review of the essential dictionary for mathematics. Writing techniques are developed gradually, from the small to the large: words, phrases, sentences, paragraphs, to end with short compositions. These may represent the introduction of a concept, the abstract of a presentation or the proof of a theorem. Along the way the student will learn how to establish a coherent notation, mix words and symbols effectively, write neat formulae, and structure a definition. Some elements of logic and all common methods of proofs are featured, including various versions of induction and existence proofs. The book concludes with advice on specific aspects of thesis writing (choosing of a title, composing an abstract, compiling a bibliography) illustrated by large number of real-life examples. Many exercises are included; over 150 of them have complete solutions, to facilitate self-study. Mathematical Writing will be of interest to all mathematics students who want to raise the quality of their coursework, reports, exams, and dissertations.

Introductory Statistics 2e

Introductory Statistics 2e PDF Author: Barbara Illowsky
Publisher:
ISBN:
Category : Mathematics
Languages : en
Pages : 2106

Book Description
Introductory Statistics 2e provides an engaging, practical, and thorough overview of the core concepts and skills taught in most one-semester statistics courses. The text focuses on diverse applications from a variety of fields and societal contexts, including business, healthcare, sciences, sociology, political science, computing, and several others. The material supports students with conceptual narratives, detailed step-by-step examples, and a wealth of illustrations, as well as collaborative exercises, technology integration problems, and statistics labs. The text assumes some knowledge of intermediate algebra, and includes thousands of problems and exercises that offer instructors and students ample opportunity to explore and reinforce useful statistical skills. This is an adaptation of Introductory Statistics 2e by OpenStax. You can access the textbook as pdf for free at openstax.org. Minor editorial changes were made to ensure a better ebook reading experience. Textbook content produced by OpenStax is licensed under a Creative Commons Attribution 4.0 International License.

Mathematical Foundations for Data Analysis

Mathematical Foundations for Data Analysis PDF Author: Jeff M. Phillips
Publisher: Springer Nature
ISBN: 3030623416
Category : Mathematics
Languages : en
Pages : 299

Book Description
This textbook, suitable for an early undergraduate up to a graduate course, provides an overview of many basic principles and techniques needed for modern data analysis. In particular, this book was designed and written as preparation for students planning to take rigorous Machine Learning and Data Mining courses. It introduces key conceptual tools necessary for data analysis, including concentration of measure and PAC bounds, cross validation, gradient descent, and principal component analysis. It also surveys basic techniques in supervised (regression and classification) and unsupervised learning (dimensionality reduction and clustering) through an accessible, simplified presentation. Students are recommended to have some background in calculus, probability, and linear algebra. Some familiarity with programming and algorithms is useful to understand advanced topics on computational techniques.

Mathematics for Machine Learning

Mathematics for Machine Learning PDF Author: Marc Peter Deisenroth
Publisher: Cambridge University Press
ISBN: 1108569323
Category : Computers
Languages : en
Pages : 392

Book Description
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.
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