Mathematica 7 Tutorial

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  mathematica 7 tutorial: The MATHEMATICA ® Book, Version 3 Stephen Wolfram, 1996-07-13 With over a million users around the world, the Mathematica ® software system created by Stephen Wolfram has defined the direction of technical computing for nearly a decade. With its major new document and computer language technology, the new version, Mathematica 3.0 takes the top-power capabilities of Mathematica and make them accessible to a vastly broader audience. This book presents this revolutionary new version of Mathematica. The Mathematica Book is a must-have purchase for anyone who wants to understand the revolutionary opportunities in science, technology, business and education made possible by Mathematica 3.0. This encompasses a broad audience of scientists and mathematicians; engineers; computer professionals; quantitative financial analysts; medical researchers; and students at high-school, college and graduate levels. Written by the creator of the system, The Mathematica Book includes both a tutorial introduction and complete reference information, and contains a comprehensive description of how to take advantage of Mathematica's ability to solve myriad technical computing problems and its powerful graphical and typesetting capabilities. Like previous editions, the book is sure to be found well-thumbed on the desks of many technical professionals and students around the world.
  mathematica 7 tutorial: Hands-on Start to Wolfram Mathematica Cliff Hastings, Kelvin Mischo, Michael Morrison, 2015 For more than 25 years, Mathematica has been the principal computation environment for millions of innovators, educators, students, and others around the world. This book is an introduction to Mathematica. The goal is to provide a hands-on experience introducing the breadth of Mathematica, with a focus on ease of use. Readers get detailed instruction with examples for interactive learning and end-of-chapter exercises. Each chapter also contains authors tips from their combined 50+ years of Mathematica use.
  mathematica 7 tutorial: Calculus Using Mathematica K.D. Stroyan, 2014-05-10 Calculus Using Mathematica: Scientific Projects and Mathematical Background is a companion to the core text, Calculus Using Mathematica. The book contains projects that illustrate applications of calculus to a variety of practical situations. The text consists of 14 chapters of various projects on how to apply the concepts and methodologies of calculus. Chapters are devoted to epidemiological applications; log and exponential functions in science; applications to mechanics, optics, economics, and ecology. Applications of linear differential equations; forced linear equations; differential equations from vector geometry; and to chemical reactions are presented as well. College students of calculus will find this book very helpful.
  mathematica 7 tutorial: Programming with Mathematica® Paul Wellin, 2013-01-10 This practical, example-driven introduction teaches the foundations of the Mathematica language so it can be applied to solving concrete problems.
  mathematica 7 tutorial: Mathematica Navigator Heikki Ruskeepaa, Heikki Ruskeepää, 2004-02-06 Mathematica Navigator gives you a general introduction to Mathematica. The book emphasizes graphics, methods of applied mathematics and statistics, and programming. Mathematica Navigator can be used both as a tutorial and as a handbook. While no previous experience with Mathematica is required, most chapters also include advanced material, so that the book will be a valuable resource for both beginners and experienced users.
  mathematica 7 tutorial: The Student's Introduction to Mathematica and the Wolfram Language Bruce F. Torrence, Eve A. Torrence, 2019-05-16 An introduction to Mathematica® and the Wolfram Language(TM) in the familiar context of the standard university mathematics curriculum.
  mathematica 7 tutorial: Mathematical Statistics with Mathematica Colin Rose, Murray D. Smith, 2002 This text and software package presents a unified approach for doing mathematical statistics with Mathematica. The mathStatica software empowers the student with the ability to solve difficult problems. The professional statistician should be able to tackle tricky multivariate distributions, generating functions, inversion theorems, symbolic maximum likelihood estimation, unbiased estimation, and the checking and correcting of textbook formulae. This is the ideal companion for researchers and students in statistics, econometrics, engineering, physics, psychometrics, economics, finance, biometrics, and the social sciences. The mathStatica CD-ROM includes: mathStatica - the applications pack for mathematical statistics, custom Mathematica palettes, live interactive book that is identical to the printed text, online help, and a trial version of Mathematica 4.0.
  mathematica 7 tutorial: The Student's Introduction to MATHEMATICA ® Bruce F. Torrence, Eve A. Torrence, 2009-01-29 The unique feature of this compact student's introduction is that it presents concepts in an order that closely follows a standard mathematics curriculum, rather than structure the book along features of the software. As a result, the book provides a brief introduction to those aspects of the Mathematica software program most useful to students. The second edition of this well loved book is completely rewritten for Mathematica 6 including coverage of the new dynamic interface elements, several hundred exercises and a new chapter on programming. This book can be used in a variety of courses, from precalculus to linear algebra. Used as a supplementary text it will aid in bridging the gap between the mathematics in the course and Mathematica. In addition to its course use, this book will serve as an excellent tutorial for those wishing to learn Mathematica and brush up on their mathematics at the same time.
  mathematica 7 tutorial: Mathematica Stephen Wolfram, 1991 Just out, the long-waited Release 2.0 of Mathematica. This new edition of the complete reference was released simultaneously and covers all the new features of Release 2.0. Includes a comprehensive review of the increased functionality of the program. Annotation copyrighted by Book News, Inc., Portland, OR
  mathematica 7 tutorial: Statistics with Mathematica Martha L. Abell, James P. Braselton, John A. Rafter, 1999 Covers the use of Mathematica for applications ranging from descriptive statistics, through multiple regression and nonparametric methods; uses virtually all of Mathematica's built-in statistical commands, as well as those contained in various Mathematica packages; Additionally, the authors have written numerous procedures to extend Mathematica's capabilities, which are also included on the CD-ROM
  mathematica 7 tutorial: Essentials of Mathematica Nino Boccara, 2007-10-17 Essential Mathematica: With Applications to Mathematics and Physics, based on the lecture notes of a course taught at the University of Illinois at Chicago to advanced undergrad and graduate students, teaches how to use Mathematica to solve a wide variety problems in mathematics and physics. It is illustrated with many detailed examples that require the student to construct meticulous, step-by-step, easy to read Mathematica programs. The first section, in which the reader learns how to use a variety of Mathematica commands, avoids long discussions and overly sophisticated techniques. Its aim is to provide the reader with Mathematica proficiency quickly and efficiently. The second section covers a broad range of applications in physics, engineering and applied mathematics, including Egyptian Fractions, Happy Numbers, Mersenne Numbers, Multibases, Quantum Harmonic Oscillator, Quantum Square Potential, Van der Pol Oscillator, Electrostatics, Motion of a Charged Particle inan Electromagnetic Field, Duffing Oscillator, Negative and Complex Bases, Tautochrone Curves, Kepler’s Laws, Foucault’s Pendulum, Iterated Function Systems, Public-Key Encryption, and Julia and Mandelbrot Sets. The first part - examples, not long explanations. The second part-attractive applications.
  mathematica 7 tutorial: Mathematica Graphics Tom Wickham-Jones, 1994-11-04 Since its first release in 1988, Mathematica has sold over a quarter of a million copies throughout the world, enabling the manipulation of fields of mathematics such as numerics, symbolic algebra, and graphics. This step-by-step guide deals solely with generating computer graphics using the Mathematica software. It is written by an expert in the field, himself an employee of Wolfram Research, Inc., the creators and distributors of the software. Dr. Wickham-Jones is directly involved in all the technical issues and programs relating to the graphics side of the Mathematica package, and is therefore an obvious choice as author of such a publication.
  mathematica 7 tutorial: Mathematica in Action Stan Wagon, S. Wagon, 1999 Mathematica in Action, 2nd Edition, is designed both as a guide to the extraordinary capabilities of Mathematica as well as a detailed tour of modern mathematics by one of its leading expositors, Stan Wagon. Ideal for teachers, researchers, mathematica enthusiasts. This second edition of the highly sucessful W.H. Freeman version includes an 8 page full color insert and 50% new material all organized around Elementary Topics, Intermediate Applications, and Advanced Projects. In addition, the book uses Mathematica 3.0 throughtout. Mathematica 3.0 notebooks with all the programs and examples discussed in the book are available on the TELOS web site (www.telospub.com). These notebooks contain materials suitable for DOS, Windows, Macintosh and Unix computers. Stan Wagon is well-known in the mathematics (and Mathematica) community as Associate Editor of the American Mathematical Monthly, a columnist for the Mathematical Intelligencer and Mathematica in Education and Research, author of The Banach-Tarski Paradox and Unsolved Problems in Elementary Geometry and Number Theory (with Victor Klee), as well as winner of the 1987 Lester R. Ford Award for Expository Writing.
  mathematica 7 tutorial: A Crash Course in Mathematica Stephan Kaufmann, 2012-12-06 A Crash Course in Mathematica is a compact introduction to the program Mathematica, which is widely used in mathematics, as well as in the natural and engineering sciences.
  mathematica 7 tutorial: Mathematica Nancy Blachman, Colin P. Williams, 1999 This book brings together reviews and methods including, system-directed approaches using small molecules, the design of target-focused compound libraries, the study of molecular selectivity, and the systematic analysis of target-ligand interactions.
  mathematica 7 tutorial: Linear Programming Robert J Vanderbei, 2013-07-16 This Fourth Edition introduces the latest theory and applications in optimization. It emphasizes constrained optimization, beginning with a substantial treatment of linear programming and then proceeding to convex analysis, network flows, integer programming, quadratic programming, and convex optimization. Readers will discover a host of practical business applications as well as non-business applications. Topics are clearly developed with many numerical examples worked out in detail. Specific examples and concrete algorithms precede more abstract topics. With its focus on solving practical problems, the book features free C programs to implement the major algorithms covered, including the two-phase simplex method, primal-dual simplex method, path-following interior-point method, and homogeneous self-dual methods. In addition, the author provides online JAVA applets that illustrate various pivot rules and variants of the simplex method, both for linear programming and for network flows. These C programs and JAVA tools can be found on the book's website. The website also includes new online instructional tools and exercises.
  mathematica 7 tutorial: Mathematics for Machine Learning Marc Peter Deisenroth, A. Aldo Faisal, Cheng Soon Ong, 2020-04-23 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.
  mathematica 7 tutorial: Mathematica DeMYSTiFied Jim Hoste, 2008-12-01 Need to learn MATHEMATICA? Problem SOLVED! Take full advantage of all the powerful capabilities of Mathematica with help from this hands-on guide. Filled with examples and step-by-step explanations, Mathematica Demystified takes you from your very first calculation all the way to plotting complex fractals. Using an intuitive format, this book explains the fundamentals of Mathematica up front. Learn how to define functions, create 2-D graphs of functions, write basic programs, and use modules. You'll move on to 3-D graphics, calculus, polynomial, linear, and differential equations, dynamical systems, and fractals. Hundreds of examples with concise explanations make it easy to understand the material, and end-of-chapter quizzes and a final exam help reinforce learning. This self-teaching guide offers: A quick way to get up and running on Mathematica Coverage of Mathematica 6 and 7 Tips for avoiding and correcting syntax errors Details on creating slideshow presentations of your work No unnecessary technical jargon A time-saving approach to performing better on an exam or at work! Simple enough for a beginner, but challenging enough for an advanced user, Mathematica Demystified is your shortcut to mastering this fully integrated technical computing software.
  mathematica 7 tutorial: Control Theory Tutorial Steven A. Frank, 2018-05-29 This open access Brief introduces the basic principles of control theory in a concise self-study guide. It complements the classic texts by emphasizing the simple conceptual unity of the subject. A novice can quickly see how and why the different parts fit together. The concepts build slowly and naturally one after another, until the reader soon has a view of the whole. Each concept is illustrated by detailed examples and graphics. The full software code for each example is available, providing the basis for experimenting with various assumptions, learning how to write programs for control analysis, and setting the stage for future research projects. The topics focus on robustness, design trade-offs, and optimality. Most of the book develops classical linear theory. The last part of the book considers robustness with respect to nonlinearity and explicitly nonlinear extensions, as well as advanced topics such as adaptive control and model predictive control. New students, as well as scientists from other backgrounds who want a concise and easy-to-grasp coverage of control theory, will benefit from the emphasis on concepts and broad understanding of the various approaches. Electronic codes for this title can be downloaded from https://extras.springer.com/?query=978-3-319-91707-8
  mathematica 7 tutorial: Computer Science with MATHEMATICA ® Roman Maeder, Roman E. Maeder, 2000-02-28 This introductory course shows scientists and engineers how Mathematica can be used to do scientific computations.
  mathematica 7 tutorial: A Student's Guide to Fourier Transforms J. F. James, 2002-09-19 Fourier transform theory is of central importance in a vast range of applications in physical science, engineering, and applied mathematics. This new edition of a successful student text provides a concise introduction to the theory and practice of Fourier transforms, using qualitative arguments wherever possible and avoiding unnecessary mathematics. After a brief description of the basic ideas and theorems, the power of the technique is then illustrated by referring to particular applications in optics, spectroscopy, electronics and telecommunications. The rarely discussed but important field of multi-dimensional Fourier theory is covered, including a description of computer-aided tomography (CAT-scanning). The final chapter discusses digital methods, with particular attention to the fast Fourier transform. Throughout, discussion of these applications is reinforced by the inclusion of worked examples. The book assumes no previous knowledge of the subject, and will be invaluable to students of physics, electrical and electronic engineering, and computer science.
  mathematica 7 tutorial: Bayesian Logical Data Analysis for the Physical Sciences Phil Gregory, 2005-04-14 Bayesian inference provides a simple and unified approach to data analysis, allowing experimenters to assign probabilities to competing hypotheses of interest, on the basis of the current state of knowledge. By incorporating relevant prior information, it can sometimes improve model parameter estimates by many orders of magnitude. This book provides a clear exposition of the underlying concepts with many worked examples and problem sets. It also discusses implementation, including an introduction to Markov chain Monte-Carlo integration and linear and nonlinear model fitting. Particularly extensive coverage of spectral analysis (detecting and measuring periodic signals) includes a self-contained introduction to Fourier and discrete Fourier methods. There is a chapter devoted to Bayesian inference with Poisson sampling, and three chapters on frequentist methods help to bridge the gap between the frequentist and Bayesian approaches. Supporting Mathematica® notebooks with solutions to selected problems, additional worked examples, and a Mathematica tutorial are available at www.cambridge.org/9780521150125.
  mathematica 7 tutorial: Generative Art Matt Pearson, 2011-06-29 Summary Generative Art presents both the technique and the beauty of algorithmic art. The book includes high-quality examples of generative art, along with the specific programmatic steps author and artist Matt Pearson followed to create each unique piece using the Processing programming language. About the Technology Artists have always explored new media, and computer-based artists are no exception. Generative art, a technique where the artist creates print or onscreen images by using computer algorithms, finds the artistic intersection of programming, computer graphics, and individual expression. The book includes a tutorial on Processing, an open source programming language and environment for people who want to create images, animations, and interactions. About the Book Generative Art presents both the techniques and the beauty of algorithmic art. In it, you'll find dozens of high-quality examples of generative art, along with the specific steps the author followed to create each unique piece using the Processing programming language. The book includes concise tutorials for each of the technical components required to create the book's images, and it offers countless suggestions for how you can combine and reuse the various techniques to create your own works. Purchase of the print book comes with an offer of a free PDF, ePub, and Kindle eBook from Manning. Also available is all code from the book. What's Inside The principles of algorithmic art A Processing language tutorial Using organic, pseudo-random, emergent, and fractal processes ========================================​========= Table of Contents Part 1 Creative Coding Generative Art: In Theory and Practice Processing: A Programming Language for ArtistsPart 2 Randomness and Noise The Wrong Way to Draw A Line The Wrong Way to Draw a Circle Adding Dimensions Part 3 Complexity Emergence Autonomy Fractals
  mathematica 7 tutorial: Introduction to GNU Octave Jason Lachniet, 2018-11-21 A brief introduction to scientific computing with GNU Octave. Designed as a textbook supplement for freshman and sophomore level linear algebra and calculus students.
  mathematica 7 tutorial: CRC Standard Curves and Surfaces David H. von Seggern, 1992-12-15 CRC Standard Curves and Surfaces is a comprehensive illustrated catalog of curves and surfaces of geometric figures and algebraic, transcendental, and integral equations used in elementary and advanced mathematics. More than 800 graphics images are featured. Based on the successful CRC Handbook of Mathematical Curves and Surfaces, this new volume retains the easy to use catalog format of the original book. Illustrations are presented in a common format organized by type of equation. Associated equations are printed in their simplest form along with any notes required to understand the illustrations. Equations and graphics appear in a side-by-side format, with figures printed on righthand pages and text on lefthand pages. Most curves and surfaces are plotted with several parameter selections so that the variation of the mathematical functions are easily understandable. Coverage on algebraic surfaces and transcendental surfaces has been expanded by 30% over the original edition; material on functions in mathematical physics has expanded by 50%. New material on functions of random processes and functions of complex variable surfaces has been added. A complementary software program (see the next title listed in this catalog) enables you to plot all of the functions found in this book.
  mathematica 7 tutorial: An Engineer's Guide to Mathematica Edward B. Magrab, 2014-05-05 Free Mathematica 10 Update Included! Now available from www.wiley.com/go/magrab Updated material includes: - Creating regions and volumes of arbitrary shape and determining their properties: arc length, area, centroid, and area moment of inertia - Performing integrations, solving equations, and determining the maximum and minimum values over regions of arbitrary shape - Solving numerically a class of linear second order partial differential equations in regions of arbitrary shape using finite elements An Engineer's Guide to Mathematica enables the reader to attain the skills to create Mathematica 9 programs that solve a wide range of engineering problems and that display the results with annotated graphics. This book can be used to learn Mathematica, as a companion to engineering texts, and also as a reference for obtaining numerical and symbolic solutions to a wide range of engineering topics. The material is presented in an engineering context and the creation of interactive graphics is emphasized. The first part of the book introduces Mathematica's syntax and commands useful in solving engineering problems. Tables are used extensively to illustrate families of commands and the effects that different options have on their output. From these tables, one can easily determine which options will satisfy one's current needs. The order of the material is introduced so that the engineering applicability of the examples increases as one progresses through the chapters. The second part of the book obtains solutions to representative classes of problems in a wide range of engineering specialties. Here, the majority of the solutions are presented as interactive graphics so that the results can be explored parametrically. Key features: Material is based on Mathematica 9 Presents over 85 examples on a wide range of engineering topics, including vibrations, controls, fluids, heat transfer, structures, statistics, engineering mathematics, and optimization Each chapter contains a summary table of the Mathematica commands used for ease of reference Includes a table of applications summarizing all of the engineering examples presented. Accompanied by a website containing Mathematica notebooks of all the numbered examples An Engineer's Guide to Mathematica is a must-have reference for practitioners, and graduate and undergraduate students who want to learn how to solve engineering problems with Mathematica.
  mathematica 7 tutorial: Using Mathematica for Quantum Mechanics Roman Schmied, 2019-09-28 This book revisits many of the problems encountered in introductory quantum mechanics, focusing on computer implementations for finding and visualizing analytical and numerical solutions. It subsequently uses these implementations as building blocks to solve more complex problems, such as coherent laser-driven dynamics in the Rubidium hyperfine structure or the Rashba interaction of an electron moving in 2D. The simulations are highlighted using the programming language Mathematica. No prior knowledge of Mathematica is needed; alternatives, such as Matlab, Python, or Maple, can also be used.
  mathematica 7 tutorial: The Mathematica Handbook Martha L Abell, James P. Braselton, 2014-05-09 The Mathematica Handbook provides all the Mathematica commands and objects along with typical examples of them. This handbook is intended as a reference of all built-in Mathematica Version 2.0 objects to both beginning and advanced users of Mathematica. The book contains commands and examples of those commands found in the packages of Mathematica, a system for doing mathematics on a computer. The Preface describes how to use the entries of The Handbook and then briefly discusses elementary rules of Mathematica syntax, defining functions, and using commands that are contained in the standard Mathematica packages. Subsequent chapters provide commands for calculations in Calculus, Statistics, and Numerical Math. The commands in these sections are listed within each package, and the packages are listed alphabetically within each folder (or directory) as well. The book will be of use to engineers, computer scientists, physical scientists, mathematicians, business professionals, and students.
  mathematica 7 tutorial: Front-End Vision and Multi-Scale Image Analysis Bart M. Haar Romeny, 2008-10-24 Many approaches have been proposed to solve the problem of finding the optic flow field of an image sequence. Three major classes of optic flow computation techniques can discriminated (see for a good overview Beauchemin and Barron IBeauchemin19951): gradient based (or differential) methods; phase based (or frequency domain) methods; correlation based (or area) methods; feature point (or sparse data) tracking methods; In this chapter we compute the optic flow as a dense optic flow field with a multi scale differential method. The method, originally proposed by Florack and Nielsen [Florack1998a] is known as the Multiscale Optic Flow Constrain Equation (MOFCE). This is a scale space version of the well known computer vision implementation of the optic flow constraint equation, as originally proposed by Horn and Schunck [Horn1981]. This scale space variation, as usual, consists of the introduction of the aperture of the observation in the process. The application to stereo has been described by Maas et al. [Maas 1995a, Maas 1996a]. Of course, difficulties arise when structure emerges or disappears, such as with occlusion, cloud formation etc. Then knowledge is needed about the processes and objects involved. In this chapter we focus on the scale space approach to the local measurement of optic flow, as we may expect the visual front end to do. 17. 2 Motion detection with pairs of receptive fields As a biologically motivated start, we begin with discussing some neurophysiological findings in the visual system with respect to motion detection.
  mathematica 7 tutorial: Mathematica by Example Martha L Abell, James P. Braselton, 2014-05-09 Mathematica by Example presents the commands and applications of Mathematica, a system for doing mathematics on a computer. This text serves as a guide to beginning users of Mathematica and users who do not intend to take advantage of the more specialized applications of Mathematica. The book combines symbolic manipulation, numerical mathematics, outstanding graphics, and a sophisticated programming language. It is comprised of 10 chapters. Chapter 1 gives a brief background of the software and how to install it in the computer. Chapter 2 introduces the essential commands of Mathematica. Basic operations on numbers, expressions, and functions are introduced and discussed. Chapter 3 provides Mathematica's built-in calculus commands. The fourth chapter presents elementary operations on lists and tables. This chapter is a prerequisite for Chapter 5 which discusses nested lists and tables in detail. The purpose of Chapter 6 is to illustrate various computations Mathematica can perform when solving differential equations. Chapters 7, 8, and 9 introduce Mathematica Packages that are not found in most Mathematica reference book. The final chapter covers the Mathematica Help feature. Engineers, computer scientists, physical scientists, mathematicians, business professionals, and students will find the book useful.
  mathematica 7 tutorial: Micromechanics with Mathematica Seiichi Nomura, 2016-05-02 Demonstrates the simplicity and effectiveness of Mathematica as the solution to practical problems in composite materials. Designed for those who need to learn how micromechanical approaches can help understand the behaviour of bodies with voids, inclusions, defects, this book is perfect for readers without a programming background. Thoroughly introducing the concept of micromechanics, it helps readers assess the deformation of solids at a localized level and analyse a body with microstructures. The author approaches this analysis using the computer algebra system Mathematica, which facilitates complex index manipulations and mathematical expressions accurately. The book begins by covering the general topics of continuum mechanics such as coordinate transformations, kinematics, stress, constitutive relationship and material symmetry. Mathematica programming is also introduced with accompanying examples. In the second half of the book, an analysis of heterogeneous materials with emphasis on composites is covered. Takes a practical approach by using Mathematica, one of the most popular programmes for symbolic computation Introduces the concept of micromechanics with worked-out examples using Mathematica code for ease of understanding Logically begins with the essentials of the topic, such as kinematics and stress, before moving to more advanced areas Applications covered include the basics of continuum mechanics, Eshelby's method, analytical and semi-analytical approaches for materials with inclusions (composites) in both infinite and finite matrix media and thermal stresses for a medium with inclusions, all with Mathematica examples Features a problem and solution section on the book’s companion website, useful for students new to the programme
  mathematica 7 tutorial: Introduction to Mathematica® for Physicists Andrey Grozin, 2015-08-21 The basics of computer algebra and the language of Mathematica are described. This title will lead toward an understanding of Mathematica that allows the reader to solve problems in physics, mathematics, and chemistry. Mathematica is the most widely used system for doing mathematical calculations by computer, including symbolic and numeric calculations and graphics. It is used in physics and other branches of science, in mathematics, education and many other areas. Many important results in physics would never be obtained without a wide use of computer algebra.
  mathematica 7 tutorial: Bayesian Data Analysis, Third Edition Andrew Gelman, John B. Carlin, Hal S. Stern, David B. Dunson, Aki Vehtari, Donald B. Rubin, 2013-11-01 Now in its third edition, this classic book is widely considered the leading text on Bayesian methods, lauded for its accessible, practical approach to analyzing data and solving research problems. Bayesian Data Analysis, Third Edition continues to take an applied approach to analysis using up-to-date Bayesian methods. The authors—all leaders in the statistics community—introduce basic concepts from a data-analytic perspective before presenting advanced methods. Throughout the text, numerous worked examples drawn from real applications and research emphasize the use of Bayesian inference in practice. New to the Third Edition Four new chapters on nonparametric modeling Coverage of weakly informative priors and boundary-avoiding priors Updated discussion of cross-validation and predictive information criteria Improved convergence monitoring and effective sample size calculations for iterative simulation Presentations of Hamiltonian Monte Carlo, variational Bayes, and expectation propagation New and revised software code The book can be used in three different ways. For undergraduate students, it introduces Bayesian inference starting from first principles. For graduate students, the text presents effective current approaches to Bayesian modeling and computation in statistics and related fields. For researchers, it provides an assortment of Bayesian methods in applied statistics. Additional materials, including data sets used in the examples, solutions to selected exercises, and software instructions, are available on the book’s web page.
  mathematica 7 tutorial: Exploring Analytic Geometry with Mathematica Donald L. Vossler, 2000 The study of two-dimensional analytic geometry has gone in and out of fashion several times over the past century, however this classic field of mathematics has once again become popular due to the growing power of personal computers and the availability of powerful mathematical software systems, such as Mathematica, that can provide an interactive environment for studying the field. By combining the power of Mathematica with an analytic geometry software system called Descarta2D, the author has succeeded in meshing an ancient field of study with modern computational tools, the result being a simple, yet powerful, approach to studying analytic geometry. Students, engineers and mathematicians alike who are interested in analytic geometry can use this book and software for the study, research or just plain enjoyment of analytic geometry. Mathematica provides an attractive environment for studying analytic geometry. Mathematica supports both numeric and symbolic computations meaning that geometry problems can be solved for special cases using numbers, as well as general cases producing formulas. Mathematica also has good facilities for producing graphical plots which are useful for visualizing the graphs of two-dimensional geometry. * A classic study in analytic geometry, complete with in-line Mathematica dialogs illustrating every concept as it is introduced * Excellent theoretical presentation *Fully explained examples of all key concepts * Interactive Mathematica notebooks for the entire book * Provides a complete computer-based environment for study of analytic geometry * All chapters and reference material are provided on CD-ROM in addition to being printedin the book * Complete software system: Descarta2D * A software system, including source code, for the underlying computer implementation, called Descarta2D is provided * Part VII of the book is a listing of the (30) Mathematica files supporting Descarta2D; the source code is also supplied on CD-ROM * Explorations * More than 120 challenging problems in analytic geometry are posed; Complete solutions are provided both as interactive Mathematica notebooks on CD-ROM and as printed material in the book * Mathematica and Descarta2D Hints expand the reader's knowledge and understanding of Descarta2D and Mathematica * Sortware developed with Mathematica 3.0 and is compatible with Mathematica 4.0 * Detailed reference manual * Complete documentation for Descarta2D * Fully integrated into the Mathematica Help Browser
  mathematica 7 tutorial: A Guide to MATLAB Brian R. Hunt, Ronald L. Lipsman, Jonathan M. Rosenberg, 2001-08-06 This book is a short, focused introduction to MATLAB and should be useful to both beginning and experienced users.
  mathematica 7 tutorial: Modern Robotics Kevin M. Lynch, Frank C. Park, 2017-05-25 This introduction to robotics offers a distinct and unified perspective of the mechanics, planning and control of robots. Ideal for self-learning, or for courses, as it assumes only freshman-level physics, ordinary differential equations, linear algebra and a little bit of computing background. Modern Robotics presents the state-of-the-art, screw-theoretic techniques capturing the most salient physical features of a robot in an intuitive geometrical way. With numerous exercises at the end of each chapter, accompanying software written to reinforce the concepts in the book and video lectures aimed at changing the classroom experience, this is the go-to textbook for learning about this fascinating subject.
  mathematica 7 tutorial: Simulating Neural Networks with Mathematica James A. Freeman, 1994 An introduction to neural networks, their operation and their application, in the context of Mathematica, a mathematical programming language. Feature show how to simulate neural network operations using Mathematica and illustrates the techniques for employing Mathematics to assess neural network behaviour and performance.
  mathematica 7 tutorial: The LaTeX Companions , 2004
  mathematica 7 tutorial: Introduction to Mathematical Thinking Keith J. Devlin, 2012 Mathematical thinking is not the same as 'doing math'--unless you are a professional mathematician. For most people, 'doing math' means the application of procedures and symbolic manipulations. Mathematical thinking, in contrast, is what the name reflects, a way of thinking about things in the world that humans have developed over three thousand years. It does not have to be about mathematics at all, which means that many people can benefit from learning this powerful way of thinking, not just mathematicians and scientists.--Back cover.
  mathematica 7 tutorial: N-Gen Math 7 Bundle - 20 Kirk Weiler, 2021-10
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