Download or read book A First Course in Probability for Computer and Data Science written by H. C. Tijms and published by World Scientific Publishing Company. This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this undergraduate text, the author has distilled the core of probabilistic ideas and methods for computer and data science. The book emphasizes probabilistic and computational thinking rather than theorems and proofs. It provides insights and motivates the students by telling them why probability works and how to apply it.The unique features of the book are as follows: This book contains many worked examples. Numerous instructive problems scattered throughout the text are given along with problem-solving strategies. Several of the problems extend previously covered material. Answers to all problems and worked-out solutions to selected problems are also provided.Henk Tijms is the author of several textbooks in the area of applied probability and stochastic optimization. In 2008, he received the prestigious INFORMS Expository Writing Award for his work. He also contributed engaging probability puzzles to The New York Times' former Numberplay column

Download or read book A First Course In Probability For Computer And Data Science written by Henk Tijms and published by World Scientific. This book was released on 2023-06-20 with total page 244 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this undergraduate text, the author has distilled the core of probabilistic ideas and methods for computer and data science. The book emphasizes probabilistic and computational thinking rather than theorems and proofs. It provides insights and motivates the students by telling them why probability works and how to apply it.The unique features of the book are as follows:This book contains many worked examples. Numerous instructive problems scattered throughout the text are given along with problem-solving strategies. Several of the problems extend previously covered material. Answers to all problems and worked-out solutions to selected problems are also provided.Henk Tijms is the author of several textbooks in the area of applied probability and stochastic optimization. In 2008, he received the prestigious INFORMS Expository Writing Award for his work. He also contributed engaging probability puzzles to The New York Times' former Numberplay column.

Download or read book A First Course in Probability written by Sheldon M. Ross and published by . This book was released on 2002 with total page 536 pages. Available in PDF, EPUB and Kindle. Book excerpt: P. 15.

Download or read book Probability with R written by Jane M. Horgan and published by John Wiley & Sons. This book was released on 2019-12-18 with total page 522 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides a comprehensive introduction to probability with an emphasis on computing-related applications This self-contained new and extended edition outlines a first course in probability applied to computer-related disciplines. As in the first edition, experimentation and simulation are favoured over mathematical proofs. The freely down-loadable statistical programming language R is used throughout the text, not only as a tool for calculation and data analysis, but also to illustrate concepts of probability and to simulate distributions. The examples in Probability with R: An Introduction with Computer Science Applications, Second Edition cover a wide range of computer science applications, including: testing program performance; measuring response time and CPU time; estimating the reliability of components and systems; evaluating algorithms and queuing systems. Chapters cover: The R language; summarizing statistical data; graphical displays; the fundamentals of probability; reliability; discrete and continuous distributions; and more. This second edition includes: improved R code throughout the text, as well as new procedures, packages and interfaces; updated and additional examples, exercises and projects covering recent developments of computing; an introduction to bivariate discrete distributions together with the R functions used to handle large matrices of conditional probabilities, which are often needed in machine translation; an introduction to linear regression with particular emphasis on its application to machine learning using testing and training data; a new section on spam filtering using Bayes theorem to develop the filters; an extended range of Poisson applications such as network failures, website hits, virus attacks and accessing the cloud; use of new allocation functions in R to deal with hash table collision, server overload and the general allocation problem. The book is supplemented with a Wiley Book Companion Site featuring data and solutions to exercises within the book. Primarily addressed to students of computer science and related areas, Probability with R: An Introduction with Computer Science Applications, Second Edition is also an excellent text for students of engineering and the general sciences. Computing professionals who need to understand the relevance of probability in their areas of practice will find it useful.

Download or read book A First Course in Probability written by Sheldon Ross and published by . This book was released on 2018-07-30 with total page 528 pages. Available in PDF, EPUB and Kindle. Book excerpt: For upper-level to graduate courses in Probability or Probability and Statistics, for majors in mathematics, statistics, engineering, and the sciences. Explores both the mathematics and the many potential applications of probability theory A First Course in Probability is an elementary introduction to the theory of probability for students in mathematics, statistics, engineering, and the sciences. Through clear and intuitive explanations, it presents not only the mathematics of probability theory, but also the many diverse possible applications of this subject through numerous examples. The 10th Edition includes many new and updated problems, exercises, and text material chosen both for interest level and for use in building student intuition about probability. 0134753119 / 9780134753119 A First Course in Probability, 10/e

Download or read book High Dimensional Probability written by Roman Vershynin and published by Cambridge University Press. This book was released on 2018-09-27 with total page 299 pages. Available in PDF, EPUB and Kindle. Book excerpt: An integrated package of powerful probabilistic tools and key applications in modern mathematical data science.

Download or read book A First Course in Probability and Statistics written by B. L. S. Prakasa Rao and published by World Scientific. This book was released on 2009 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a clear exposition of the theory of probability along with applications in statistics.

Download or read book Probability for Data Scientists First Edition written by Juana Sánchez and published by Cognella Academic Publishing. This book was released on 2019-05-31 with total page 341 pages. Available in PDF, EPUB and Kindle. Book excerpt: Probability for Data Scientists provides students with a mathematically sound yet accessible introduction to the theory and applications of probability. Students learn how probability theory supports statistics, data science, and machine learning theory by enabling scientists to move beyond mere descriptions of data to inferences about specific populations. The book is divided into two parts. Part I introduces readers to fundamental definitions, theorems, and methods within the context of discrete sample spaces. It addresses the origin of the mathematical study of probability, main concepts in modern probability theory, univariate and bivariate discrete probability models, and the multinomial distribution. Part II builds upon the knowledge imparted in Part I to present students with corresponding ideas in the context of continuous sample spaces. It examines models for single and multiple continuous random variables and the application of probability theorems in statistics. Probability for Data Scientists effectively introduces students to key concepts in probability and demonstrates how a small set of methodologies can be applied to a plethora of contextually unrelated problems. It is well suited for courses in statistics, data science, machine learning theory, or any course with an emphasis in probability. Numerous exercises, some of which provide R software code to conduct experiments that illustrate the laws of probability, are provided in each chapter.

Download or read book A First Course in Probability written by Tapas K. Chandra and published by Alpha Science Int'l Ltd.. This book was released on 2005 with total page 520 pages. Available in PDF, EPUB and Kindle. Book excerpt: "The third edition earmarks the great success of this text among the students as well as the teachers. To enhance its utility one additional appendix on "The Theory of Errors" has been incorporated along with necessary modifications and corrections in the text. The treatment, as before, is rigorous yet impressively elegant and simple. The special feature of this text is its effort to resolve many outstanding confusions of probability and statistics. This will undoubtedly continue to be a valuable companion for all those pursuing a career in Statistics."--BOOK JACKET.

Download or read book Probability and Statistics for Computer Scientists Second Edition written by Michael Baron and published by CRC Press. This book was released on 2013-08-05 with total page 475 pages. Available in PDF, EPUB and Kindle. Book excerpt: Student-Friendly Coverage of Probability, Statistical Methods, Simulation, and Modeling Tools Incorporating feedback from instructors and researchers who used the previous edition, Probability and Statistics for Computer Scientists, Second Edition helps students understand general methods of stochastic modeling, simulation, and data analysis; make optimal decisions under uncertainty; model and evaluate computer systems and networks; and prepare for advanced probability-based courses. Written in a lively style with simple language, this classroom-tested book can now be used in both one- and two-semester courses. New to the Second Edition Axiomatic introduction of probability Expanded coverage of statistical inference, including standard errors of estimates and their estimation, inference about variances, chi-square tests for independence and goodness of fit, nonparametric statistics, and bootstrap More exercises at the end of each chapter Additional MATLAB® codes, particularly new commands of the Statistics Toolbox In-Depth yet Accessible Treatment of Computer Science-Related Topics Starting with the fundamentals of probability, the text takes students through topics heavily featured in modern computer science, computer engineering, software engineering, and associated fields, such as computer simulations, Monte Carlo methods, stochastic processes, Markov chains, queuing theory, statistical inference, and regression. It also meets the requirements of the Accreditation Board for Engineering and Technology (ABET). Encourages Practical Implementation of Skills Using simple MATLAB commands (easily translatable to other computer languages), the book provides short programs for implementing the methods of probability and statistics as well as for visualizing randomness, the behavior of random variables and stochastic processes, convergence results, and Monte Carlo simulations. Preliminary knowledge of MATLAB is not required. Along with numerous computer science applications and worked examples, the text presents interesting facts and paradoxical statements. Each chapter concludes with a short summary and many exercises.

Download or read book A First Course in Probability written by T. K. Chandra and published by . This book was released on 2001 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Probability Statistics and Data written by Darrin Speegle and published by CRC Press. This book was released on 2021-11-26 with total page 644 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a fresh approach to a calculus based, first course in probability and statistics, using R throughout to give a central role to data and simulation. The book introduces probability with Monte Carlo simulation as an essential tool. Simulation makes challenging probability questions quickly accessible and easily understandable. Mathematical approaches are included, using calculus when appropriate, but are always connected to experimental computations. Using R and simulation gives a nuanced understanding of statistical inference. The impact of departure from assumptions in statistical tests is emphasized, quantified using simulations, and demonstrated with real data. The book compares parametric and non-parametric methods through simulation, allowing for a thorough investigation of testing error and power. The text builds R skills from the outset, allowing modern methods of resampling and cross validation to be introduced along with traditional statistical techniques. Fifty-two data sets are included in the complementary R package fosdata. Most of these data sets are from recently published papers, so that you are working with current, real data, which is often large and messy. Two central chapters use powerful tidyverse tools (dplyr, ggplot2, tidyr, stringr) to wrangle data and produce meaningful visualizations. Preliminary versions of the book have been used for five semesters at Saint Louis University, and the majority of the more than 400 exercises have been classroom tested.

Download or read book Probability and Statistics for Data Science written by Norman S. Matloff and published by Chapman & Hall/CRC. This book was released on 2019 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text is designed for a one-semester junior/senior/graduate-level calculus-based course on probability and statistics, aimed specifically at data science students (including computer science). In addition to calculus, the text assumes basic knowledge of matrix algebra and rudimentary computer programming.

Download or read book Introduction to Probability and Statistics for Engineers and Scientists written by Sheldon M. Ross and published by Academic Press. This book was released on 2009-03-13 with total page 681 pages. Available in PDF, EPUB and Kindle. Book excerpt: This updated text provides a superior introduction to applied probability and statistics for engineering or science majors. Ross emphasizes the manner in which probability yields insight into statistical problems; ultimately resulting in an intuitive understanding of the statistical procedures most often used by practicing engineers and scientists. Real data sets are incorporated in a wide variety of exercises and examples throughout the book, and this emphasis on data motivates the probability coverage.As with the previous editions, Ross' text has remendously clear exposition, plus real-data examples and exercises throughout the text. Numerous exercises, examples, and applications apply probability theory to everyday statistical problems and situations. - New Chapter on Simulation, Bootstrap Statistical Methods, and Permutation Tests - 20% New Updated problem sets and applications, that demonstrate updated applications to engineering as well as biological, physical and computer science - New Real data examples that use significant real data from actual studies across life science, engineering, computing and business - New End of Chapter review material that emphasizes key ideas as well as the risks associated with practical application of the material

Download or read book A First Course in Probability written by Sheldon Ross and published by Pearson Higher Ed. This book was released on 2011-11-21 with total page 545 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the eBook of the printed book and may not include any media, website access codes, or print supplements that may come packaged with the bound book. A First Course in Probability, Eighth Edition, features clear and intuitive explanations of the mathematics of probability theory, outstanding problem sets, and a variety of diverse examples and applications. This book is ideal for an upper-level undergraduate or graduate level introduction to probability for math, science, engineering and business students. It assumes a background in elementary calculus.

Download or read book Introduction to Probability written by David F. Anderson and published by Cambridge University Press. This book was released on 2017-11-02 with total page 447 pages. Available in PDF, EPUB and Kindle. Book excerpt: This classroom-tested textbook is an introduction to probability theory, with the right balance between mathematical precision, probabilistic intuition, and concrete applications. Introduction to Probability covers the material precisely, while avoiding excessive technical details. After introducing the basic vocabulary of randomness, including events, probabilities, and random variables, the text offers the reader a first glimpse of the major theorems of the subject: the law of large numbers and the central limit theorem. The important probability distributions are introduced organically as they arise from applications. The discrete and continuous sides of probability are treated together to emphasize their similarities. Intended for students with a calculus background, the text teaches not only the nuts and bolts of probability theory and how to solve specific problems, but also why the methods of solution work.

Download or read book A First Course in Statistical Inference written by Jonathan Gillard and published by Springer Nature. This book was released on 2020-04-20 with total page 167 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a modern and accessible introduction to Statistical Inference, the science of inferring key information from data. Aimed at beginning undergraduate students in mathematics, it presents the concepts underpinning frequentist statistical theory. Written in a conversational and informal style, this concise text concentrates on ideas and concepts, with key theorems stated and proved. Detailed worked examples are included and each chapter ends with a set of exercises, with full solutions given at the back of the book. Examples using R are provided throughout the book, with a brief guide to the software included. Topics covered in the book include: sampling distributions, properties of estimators, confidence intervals, hypothesis testing, ANOVA, and fitting a straight line to paired data. Based on the author’s extensive teaching experience, the material of the book has been honed by student feedback for over a decade. Assuming only some familiarity with elementary probability, this textbook has been devised for a one semester first course in statistics.