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Statistics With Mathematica
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Book Synopsis Statistics with Mathematica by : Martha L. Abell
Download or read book Statistics with Mathematica written by Martha L. Abell and published by Academic Press. This book was released on 1999 with total page 654 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Book Synopsis Mathematical Statistics with Mathematica by : Colin Rose
Download or read book Mathematical Statistics with Mathematica written by Colin Rose and published by Springer. This book was released on 2002 with total page 508 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis An Introduction to Statistics with the Wolfram Language by : Juan H. Klopper
Download or read book An Introduction to Statistics with the Wolfram Language written by Juan H. Klopper and published by Wolfram Media Incorporated. This book was released on 2020-05-06 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Mathematica Data Analysis by : Sergiy Suchok
Download or read book Mathematica Data Analysis written by Sergiy Suchok and published by Packt Publishing Ltd. This book was released on 2015-12-24 with total page 164 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn and explore the fundamentals of data analysis with power of Mathematica About This Book Use the power of Mathematica to analyze data in your applications Discover the capabilities of data classification and pattern recognition offered by Mathematica Use hundreds of algorithms for time series analysis to predict the future Who This Book Is For The book is for those who want to learn to use the power of Mathematica to analyze and process data. Perhaps you are already familiar with data analysis but have never used Mathematica, or you know Mathematica but you are new to data analysis. With the help of this book, you will be able to quickly catch up on the key points for a successful start. What You Will Learn Import data from different sources to Mathematica Link external libraries with programs written in Mathematica Classify data and partition them into clusters Recognize faces, objects, text, and barcodes Use Mathematica functions for time series analysis Use algorithms for statistical data processing Predict the result based on the observations In Detail There are many algorithms for data analysis and it's not always possible to quickly choose the best one for each case. Implementation of the algorithms takes a lot of time. With the help of Mathematica, you can quickly get a result from the use of a particular method, because this system contains almost all the known algorithms for data analysis. If you are not a programmer but you need to analyze data, this book will show you the capabilities of Mathematica when just few strings of intelligible code help to solve huge tasks from statistical issues to pattern recognition. If you're a programmer, with the help of this book, you will learn how to use the library of algorithms implemented in Mathematica in your programs, as well as how to write algorithm testing procedure. With each chapter, you'll be more immersed in the special world of Mathematica. Along with intuitive queries for data processing, we will highlight the nuances and features of this system, allowing you to build effective analysis systems. With the help of this book, you will learn how to optimize the computations by combining your libraries with the Mathematica kernel. Style and approach This book takes a step-by-step approach, accompanied by examples, so you get a better understanding of the logic of writing algorithms for data analysis in Mathematica. We provide a detailed explanation of all the nuances of the Mathematica language, no matter what your level of experience is.
Book Synopsis Bayesian Logical Data Analysis for the Physical Sciences by : Phil Gregory
Download or read book Bayesian Logical Data Analysis for the Physical Sciences written by Phil Gregory and published by Cambridge University Press. This book was released on 2005-04-14 with total page 498 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Hands-on Start to Wolfram Mathematica by : Cliff Hastings
Download or read book Hands-on Start to Wolfram Mathematica written by Cliff Hastings and published by . This book was released on 2016 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Mathematica Navigator by : Heikki Ruskeepaa
Download or read book Mathematica Navigator written by Heikki Ruskeepaa and published by Gulf Professional Publishing. This book was released on 2004-02-06 with total page 1135 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Mathematica Laboratories for Mathematical Statistics by : Jenny A. Baglivo
Download or read book Mathematica Laboratories for Mathematical Statistics written by Jenny A. Baglivo and published by SIAM. This book was released on 2005-01-01 with total page 273 pages. Available in PDF, EPUB and Kindle. Book excerpt: CD-ROM contains text, data, computations, and graphics.
Download or read book Compstat written by Wolfgang Härdle and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 654 pages. Available in PDF, EPUB and Kindle. Book excerpt: This COMPSTAT 2002 book contains the Keynote, Invited, and Full Contributed papers presented in Berlin, August 2002. A companion volume including Short Communications and Posters is published on CD. The COMPSTAT 2002 is the 15th conference in a serie of biannual conferences with the objective to present the latest developments in Computational Statistics and is taking place from August 24th to August 28th, 2002. Previous COMPSTATs were in Vienna (1974), Berlin (1976), Leiden (1978), Edinburgh (1980), Toulouse (1982), Pra~ue (1984), Rome (1986), Copenhagen (1988), Dubrovnik (1990), Neuchatel (1992), Vienna (1994), Barcelona (1996), Bris tol (1998) and Utrecht (2000). COMPSTAT 2002 is organised by CASE, Center of Applied Statistics and Eco nomics at Humboldt-Universitat zu Berlin in cooperation with F'reie Universitat Berlin and University of Potsdam. The topics of COMPSTAT include methodological applications, innovative soft ware and mathematical developments, especially in the following fields: statistical risk management, multivariate and robust analysis, Markov Chain Monte Carlo Methods, statistics of E-commerce, new strategies in teaching (Multimedia, In ternet), computerbased sampling/questionnaires, analysis of large databases (with emphasis on computing in memory), graphical tools for data analysis, classification and clustering, new statistical software and historical development of software.
Book Synopsis Introduction to Mathematica® with Applications by : Marian Mureşan
Download or read book Introduction to Mathematica® with Applications written by Marian Mureşan and published by Springer. This book was released on 2017-02-21 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: Starting with an introduction to the numerous features of Mathematica®, this book continues with more complex material. It provides the reader with lots of examples and illustrations of how the benefits of Mathematica® can be used. Composed of eleven chapters, it includes the following: A chapter on several sorting algorithms Functions (planar and solid) with many interesting examples Ordinary differential equations Advantages of Mathematica® dealing with the Pi number The power of Mathematica® working with optimal control problems Introduction to Mathematica® with Applications will appeal to researchers, professors and students requiring a computational tool.
Book Synopsis All of Statistics by : Larry Wasserman
Download or read book All of Statistics written by Larry Wasserman and published by Springer Science & Business Media. This book was released on 2013-12-11 with total page 446 pages. Available in PDF, EPUB and Kindle. Book excerpt: Taken literally, the title "All of Statistics" is an exaggeration. But in spirit, the title is apt, as the book does cover a much broader range of topics than a typical introductory book on mathematical statistics. This book is for people who want to learn probability and statistics quickly. It is suitable for graduate or advanced undergraduate students in computer science, mathematics, statistics, and related disciplines. The book includes modern topics like non-parametric curve estimation, bootstrapping, and classification, topics that are usually relegated to follow-up courses. The reader is presumed to know calculus and a little linear algebra. No previous knowledge of probability and statistics is required. Statistics, data mining, and machine learning are all concerned with collecting and analysing data.
Book Synopsis Introduction to Probability with Mathematica by : Kevin J. Hastings
Download or read book Introduction to Probability with Mathematica written by Kevin J. Hastings and published by CRC Press. This book was released on 2009-09-21 with total page 467 pages. Available in PDF, EPUB and Kindle. Book excerpt: Updated to conform to Mathematica® 7.0, Introduction to Probability with Mathematica®, Second Edition continues to show students how to easily create simulations from templates and solve problems using Mathematica. It provides a real understanding of probabilistic modeling and the analysis of data and encourages the application of these ideas to practical problems. The accompanying CD-ROM offers instructors the option of creating class notes, demonstrations, and projects. New to the Second Edition Expanded section on Markov chains that includes a study of absorbing chains New sections on order statistics, transformations of multivariate normal random variables, and Brownian motion More example data of the normal distribution More attention on conditional expectation, which has become significant in financial mathematics Additional problems from Actuarial Exam P New appendix that gives a basic introduction to Mathematica New examples, exercises, and data sets, particularly on the bivariate normal distribution New visualization and animation features from Mathematica 7.0 Updated Mathematica notebooks on the CD-ROM (Go to Downloads/Updates tab for link to CD files.) After covering topics in discrete probability, the text presents a fairly standard treatment of common discrete distributions. It then transitions to continuous probability and continuous distributions, including normal, bivariate normal, gamma, and chi-square distributions. The author goes on to examine the history of probability, the laws of large numbers, and the central limit theorem. The final chapter explores stochastic processes and applications, ideal for students in operations research and finance.
Download or read book Statistics written by David W. Scott and published by John Wiley & Sons. This book was released on 2020-07-13 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistic: A Concise Mathematical Introduction for Students and Scientists offers a one academic term text that prepares the student to broaden their skills in statistics, probability and inference, prior to selecting their follow-on courses in their chosen fields, whether it be engineering, computer science, programming, data sciences, business or economics. The book places focus early on continuous measurements, as well as discrete random variables. By invoking simple and intuitive models and geometric probability, discrete and continuous experiments and probabilities are discussed throughout the book in a natural way. Classical probability, random variables, and inference are discussed, as well as material on understanding data and topics of special interest. Topics discussed include: • Classical equally likely outcomes • Variety of models of discrete and continuous probability laws • Likelihood function and ratio • Inference • Bayesian statistics With the growth in the volume of data generated in many disciplines that is enabling the growth in data science, companies now demand statistically literate scientists and this textbook is the answer, suited for undergraduates studying science or engineering, be it computer science, economics, life sciences, environmental, business, amongst many others. Basic knowledge of bivariate calculus, R language, Matematica and JMP is useful, however there is an accompanying website including sample R and Mathematica code to help instructors and students.
Book Synopsis Introduction to Machine Learning by : Shan-e-Fatima
Download or read book Introduction to Machine Learning written by Shan-e-Fatima and published by Blue Rose Publishers. This book was released on 2023-09-25 with total page 189 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the use of machine learning (ML), which is a form of artificial intelligence (AI), software programmers may predict outcomes more accurately without having to be explicitly instructed to do so. In order to forecast new output values, machine learning algorithms use historical data as input. Machine learning is frequently used in recommendation engines. Business process automation (BPA), predictive maintenance, spam filtering, malware threat detection, and fraud detection are a few additional common uses. Machine learning is significant because it aids in the development of new goods and provides businesses with a picture of trends in consumer behavior and operational business patterns. For many businesses, machine learning has emerged as a key competitive differentiation. The fundamental methods of machine learning are covered in the current book.
Book Synopsis Mathematical Statistics by : Jun Shao
Download or read book Mathematical Statistics written by Jun Shao and published by Springer Science & Business Media. This book was released on 2008-02-03 with total page 607 pages. Available in PDF, EPUB and Kindle. Book excerpt: This graduate textbook covers topics in statistical theory essential for graduate students preparing for work on a Ph.D. degree in statistics. This new edition has been revised and updated and in this fourth printing, errors have been ironed out. The first chapter provides a quick overview of concepts and results in measure-theoretic probability theory that are useful in statistics. The second chapter introduces some fundamental concepts in statistical decision theory and inference. Subsequent chapters contain detailed studies on some important topics: unbiased estimation, parametric estimation, nonparametric estimation, hypothesis testing, and confidence sets. A large number of exercises in each chapter provide not only practice problems for students, but also many additional results.
Book Synopsis Mathematica Cookbook by : Sal Mangano
Download or read book Mathematica Cookbook written by Sal Mangano and published by "O'Reilly Media, Inc.". This book was released on 2010-04-02 with total page 830 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mathematica Cookbook helps you master the application's core principles by walking you through real-world problems. Ideal for browsing, this book includes recipes for working with numerics, data structures, algebraic equations, calculus, and statistics. You'll also venture into exotic territory with recipes for data visualization using 2D and 3D graphic tools, image processing, and music. Although Mathematica 7 is a highly advanced computational platform, the recipes in this book make it accessible to everyone -- whether you're working on high school algebra, simple graphs, PhD-level computation, financial analysis, or advanced engineering models. Learn how to use Mathematica at a higher level with functional programming and pattern matching Delve into the rich library of functions for string and structured text manipulation Learn how to apply the tools to physics and engineering problems Draw on Mathematica's access to physics, chemistry, and biology data Get techniques for solving equations in computational finance Learn how to use Mathematica for sophisticated image processing Process music and audio as musical notes, analog waveforms, or digital sound samples
Book Synopsis Mathematical Theory of Bayesian Statistics by : Sumio Watanabe
Download or read book Mathematical Theory of Bayesian Statistics written by Sumio Watanabe and published by CRC Press. This book was released on 2018-04-27 with total page 331 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mathematical Theory of Bayesian Statistics introduces the mathematical foundation of Bayesian inference which is well-known to be more accurate in many real-world problems than the maximum likelihood method. Recent research has uncovered several mathematical laws in Bayesian statistics, by which both the generalization loss and the marginal likelihood are estimated even if the posterior distribution cannot be approximated by any normal distribution. Features Explains Bayesian inference not subjectively but objectively. Provides a mathematical framework for conventional Bayesian theorems. Introduces and proves new theorems. Cross validation and information criteria of Bayesian statistics are studied from the mathematical point of view. Illustrates applications to several statistical problems, for example, model selection, hyperparameter optimization, and hypothesis tests. This book provides basic introductions for students, researchers, and users of Bayesian statistics, as well as applied mathematicians. Author Sumio Watanabe is a professor of Department of Mathematical and Computing Science at Tokyo Institute of Technology. He studies the relationship between algebraic geometry and mathematical statistics.
