## First Course in Probability, A: Pearson New International Edition

**Author**: Sheldon Ross

**Publisher:**Pearson Higher Ed

**ISBN:**1292037563

**Category:**Mathematics

**Page:**464

**View:**1845

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A First Course in Probability, Ninth 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.

## A First Course in Probability

**Author**: Sheldon Ross

**Publisher:**N.A

**ISBN:**9781292024929

**Category:**Probabilities

**Page:**464

**View:**4087

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A First Course in Probability, Ninth 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.

## A First Course in Statistics

**Author**: James T. McClave,Terry T Sincich

**Publisher:**Pearson

**ISBN:**0134080793

**Category:**Mathematics

**Page:**624

**View:**2891

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For courses in introductory statistics. A Contemporary Classic Classic, yet contemporary; theoretical, yet applied–McClave & Sincich’s A First Course in Statistics gives you the best of both worlds. This text offers a trusted, comprehensive introduction to statistics that emphasizes inference and integrates real data throughout. The authors stress the development of statistical thinking, the assessment of credibility, and value of the inferences made from data. This new edition is extensively revised with an eye on clearer, more concise language throughout the text and in the exercises. Ideal for one- or two-semester courses in introductory statistics, this text assumes a mathematical background of basic algebra. Flexibility is built in for instructors who teach a more advanced course, with optional footnotes about calculus and the underlying theory. Also available with MyStatLab MyStatLab™ is an online homework, tutorial, and assessment program designed to work with this text to engage students and improve results. Within its structured environment, students practice what they learn, test their understanding, and pursue a personalized study plan that helps them absorb course material and understand difficult concepts. For this edition, MyStatLab offers 30% new and updated exercises. Note: You are purchasing a standalone product; MyLab™ & Mastering™ does not come packaged with this content. Students, if interested in purchasing this title with MyLab & Mastering, ask your instructor for the correct package ISBN and Course ID. Instructors, contact your Pearson representative for more information. If you would like to purchase both the physical text and MyLab & Mastering, search for: 0134090438 / 9780134090436 * Statistics Plus New MyStatLab with Pearson eText -- Access Card Package Package consists of: 0134080211 / 9780134080215 * Statistics 0321847997 / 9780321847997 * My StatLab Glue-in Access Card 032184839X / 9780321848390 * MyStatLab Inside Sticker for Glue-In Packages

## Introduction to Probability Models

**Author**: Sheldon M. Ross

**Publisher:**Elsevier

**ISBN:**1483276589

**Category:**Mathematics

**Page:**568

**View:**4005

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Introduction to Probability Models, Fifth Edition focuses on different probability models of natural phenomena. This edition includes additional material in Chapters 5 and 10, such as examples relating to analyzing algorithms, minimizing highway encounters, collecting coupons, and tracking the AIDS virus. The arbitrage theorem and its relationship to the duality theorem of linear program are also covered, as well as how the arbitrage theorem leads to the Black-Scholes option pricing formula. Other topics include the Bernoulli random variable, Chapman-Kolmogorov equations, and properties of the exponential distribution. The continuous-time Markov chains, single-server exponential queueing system, variations on Brownian motion; and variance reduction by conditioning are also elaborated. This book is a good reference for students and researchers conducting work on probability models.

## First Course in Statistics, A: Pearson New International Edition

**Author**: James T McClave,Terry Sincich

**Publisher:**Pearson Higher Ed

**ISBN:**1292036818

**Category:**Mathematics

**Page:**600

**View:**4377

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Classic, yet contemporary. Theoretical, yet applied. McClave & Sincich’s Statistics: A First Course in Statistics gives you the best of both worlds. This text offers a trusted, comprehensive introduction to statistics that emphasizes inference and integrates real data throughout. The authors stress the development of statistical thinking, the assessment of credibility, and value of the inferences made from data. The Eleventh Edition infuses a new focus on ethics, which is critically important when working with statistical data. Chapter Summaries have a new, study-oriented design, helping students stay focused when preparing for exams. Data, exercises, technology support, and Statistics in Action cases are updated throughout the book. In addition, MyStatLab will have increased exercise coverage and two new banks of questions to draw from: Getting Ready for Stats and Conceptual Question Library. Ideal for one- or two-semester courses in introductory statistics, this text assumes a mathematical background of basic algebra. Flexibility is built in for instructors who teach a more advanced course, with optional footnotes about calculus and the underlying theory.

## A First Course in Machine Learning, Second Edition

**Author**: Simon Rogers,Mark Girolami

**Publisher:**CRC Press

**ISBN:**1498738540

**Category:**Business & Economics

**Page:**427

**View:**4199

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"A First Course in Machine Learning by Simon Rogers and Mark Girolami is the best introductory book for ML currently available. It combines rigor and precision with accessibility, starts from a detailed explanation of the basic foundations of Bayesian analysis in the simplest of settings, and goes all the way to the frontiers of the subject such as infinite mixture models, GPs, and MCMC." —Devdatt Dubhashi, Professor, Department of Computer Science and Engineering, Chalmers University, Sweden "This textbook manages to be easier to read than other comparable books in the subject while retaining all the rigorous treatment needed. The new chapters put it at the forefront of the field by covering topics that have become mainstream in machine learning over the last decade." —Daniel Barbara, George Mason University, Fairfax, Virginia, USA "The new edition of A First Course in Machine Learning by Rogers and Girolami is an excellent introduction to the use of statistical methods in machine learning. The book introduces concepts such as mathematical modeling, inference, and prediction, providing ‘just in time’ the essential background on linear algebra, calculus, and probability theory that the reader needs to understand these concepts." —Daniel Ortiz-Arroyo, Associate Professor, Aalborg University Esbjerg, Denmark "I was impressed by how closely the material aligns with the needs of an introductory course on machine learning, which is its greatest strength...Overall, this is a pragmatic and helpful book, which is well-aligned to the needs of an introductory course and one that I will be looking at for my own students in coming months." —David Clifton, University of Oxford, UK "The first edition of this book was already an excellent introductory text on machine learning for an advanced undergraduate or taught masters level course, or indeed for anybody who wants to learn about an interesting and important field of computer science. The additional chapters of advanced material on Gaussian process, MCMC and mixture modeling provide an ideal basis for practical projects, without disturbing the very clear and readable exposition of the basics contained in the first part of the book." —Gavin Cawley, Senior Lecturer, School of Computing Sciences, University of East Anglia, UK "This book could be used for junior/senior undergraduate students or first-year graduate students, as well as individuals who want to explore the field of machine learning...The book introduces not only the concepts but the underlying ideas on algorithm implementation from a critical thinking perspective." —Guangzhi Qu, Oakland University, Rochester, Michigan, USA

## Introductory Statistics

**Author**: Sheldon M. Ross

**Publisher:**Academic Press

**ISBN:**012804361X

**Category:**Mathematics

**Page:**828

**View:**3510

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Introductory Statistics, Fourth Edition, reviews statistical concepts and techniques in a manner that will teach students not only how and when to utilize the statistical procedures developed, but also how to understand why these procedures should be used. The text's main merits are the clarity of presentation, contemporary examples and applications from diverse areas, an explanation of intuition, and the ideas behind the statistical methods. Concepts are motivated, illustrated, and explained in a way that attempts to increase one's intuition. To quote from the preface, it is only when a student develops a feel or intuition for statistics that she or he is really on the path toward making sense of data. Ross achieves this goal through a coherent mix of mathematical analysis, intuitive discussions, and examples. Applications and examples refer to real-world issues, such as gun control, stock price models, health issues, driving age limits, school admission ages, use of helmets, sports, scientific fraud, and many others. Examples relating to data mining techniques using the number of Google queries or Twitter tweets are also considered. For this fourth edition, new topical coverage includes sections on Pareto distribution and the 80-20 rule, Benford's law, added material on odds and joint distributions and correlation, logistic regression, A-B testing, and more modern (big data) examples and exercises. Includes new section on Pareto distribution and the 80-20 rule, Benford’s law, odds, joint distribution and correlation, logistic regression, A-B testing, and examples from the world of analytics and big data Comprehensive edition that includes the most commonly used statistical software packages (SAS, SPSS, Minitab), ISM, SSM, and an online graphing calculator manual Presents a unique, historical perspective, profiling prominent statisticians and historical events to motivate learning by including interest and context Provides exercises and examples that help guide the student towards indpendent learning using real issues and real data, e.g. stock price models, health issues, gender issues, sports, and scientific fraud

## Understanding Probability

**Author**: Henk Tijms

**Publisher:**Cambridge University Press

**ISBN:**1139511076

**Category:**Mathematics

**Page:**N.A

**View:**9334

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Understanding Probability is a unique and stimulating approach to a first course in probability. The first part of the book demystifies probability and uses many wonderful probability applications from everyday life to help the reader develop a feel for probabilities. The second part, covering a wide range of topics, teaches clearly and simply the basics of probability. This fully revised third edition has been packed with even more exercises and examples and it includes new sections on Bayesian inference, Markov chain Monte-Carlo simulation, hitting probabilities in random walks and Brownian motion, and a new chapter on continuous-time Markov chains with applications. Here you will find all the material taught in an introductory probability course. The first part of the book, with its easy-going style, can be read by anybody with a reasonable background in high school mathematics. The second part of the book requires a basic course in calculus.

## Elementary Probability

**Author**: David Stirzaker

**Publisher:**Cambridge University Press

**ISBN:**9781139441032

**Category:**Mathematics

**Page:**N.A

**View:**2678

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Now available in a fully revised and updated second edition, this well established textbook provides a straightforward introduction to the theory of probability. The presentation is entertaining without any sacrifice of rigour; important notions are covered with the clarity that the subject demands. Topics covered include conditional probability, independence, discrete and continuous random variables, basic combinatorics, generating functions and limit theorems, and an introduction to Markov chains. The text is accessible to undergraduate students and provides numerous worked examples and exercises to help build the important skills necessary for problem solving.

## A First Course in Abstract Algebra

**Author**: John B. Fraleigh

**Publisher:**Pearson Education India

**ISBN:**9788177589009

**Category:**Algebra

**Page:**520

**View:**1269

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## Student Value Edition for Business Statistics

*A First Course*

**Author**: David M. Levine

**Publisher:**Prentice Hall

**ISBN:**9780136094012

**Category:**Business & Economics

**Page:**648

**View:**3120

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Levine, Krehbiel and Bereson have teamed up once again to present statistical topics in a business-applied context. Introduction and Data Collection; Presenting Data in Tables and Charts; Numerical Descriptive Measures; Basic Probability; Some Important Discrete Probability Distributions; The Normal Distribution and Other Continuous Distributions; Sampling and Sampling Distributions; Confidence Interval Estimation; Fundamentals of Hypothesis Testing; Two Sample Tests and One-Way Anova; Chi-Square Tests; Simple Linear Regression; Multiple Regression; Statistical Applications in Quality ManagementMARKET: "Business Statistics: A First Course "comprehensibly provides readers with the information they need to know in order to understand, apply, and utilize statistical data from a business perspective.

## An Introduction to Mathematical Statistics and Its Applications

**Author**: Richard J. Larsen,Morris L. Marx

**Publisher:**Pearson

**ISBN:**0134114248

**Category:**Mathematics

**Page:**768

**View:**4599

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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. For courses in Mathematical Statistics Introducing the principles of statistics and data modeling Introduction to Mathematical Statistics and Its Applications , 6th Edition is a high-level calculus student’s first exposure to mathematical statistics. This book provides students who have already taken three or more semesters of calculus with the background to apply statistical principles. Meaty enough to guide a two-semester course, the book touches on both statistics and experimental design, which teaches students various ways to analyze data. It gives computational-minded students a necessary and realistic exposure to identifying data models.

## Probability: A Lively Introduction

**Author**: Henk Tijms

**Publisher:**Cambridge University Press

**ISBN:**1108418740

**Category:**Mathematics

**Page:**N.A

**View:**5045

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Comprehensive, yet concise, this textbook is the go-to guide to learn why probability is so important and its applications.

## Mendenhall

*2nd Crs Regrs Anl PNIE_7*

**Author**: William Mendenhall,Terry Sincich

**Publisher:**Pearson

**ISBN:**9781292042909

**Category:**Commercial statistics

**Page:**748

**View:**5060

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The Second Course in Statistics is an increasingly important offering since more students are arriving at college having taken AP Statistics in high school. Mendenhall/Sincich's A Second Course in Statistics is the perfect book for courses that build on the knowledge students gain in AP Statistics, or the freshman Introductory Statistics course. A Second Course in Statistics: Regression Analysis, Seventh Edition, focuses on building linear statistical models and developing skills for implementing regression analysis in real situations. This text offers applications for engineering, sociology, psychology, science, and business. The authors use real data and scenarios extracted from news articles, journals, and actual consulting problems to show how to apply the concepts. In addition, seven case studies, now located throughout the text after applicable chapters, invite students to focus on specific problems, and are suitable for class discussion.

## Data Analysis with SPSS

*A First Course in Applied Statistics*

**Author**: Stephen A. Sweet,Karen Grace-Martin

**Publisher:**Prentice Hall

**ISBN:**9780205863723

**Category:**Computers

**Page:**288

**View:**765

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ALERT: Before you purchase, check with your instructor or review your course syllabus to ensure that you select the correct ISBN. Several versions of Pearson's MyLab & Mastering products exist for each title, including customized versions for individual schools, and registrations are not transferable. In addition, you may need a CourseID, provided by your instructor, to register for and use Pearson's MyLab & Mastering products. Packages Access codes for Pearson's MyLab & Mastering products may not be included when purchasing or renting from companies other than Pearson; check with the seller before completing your purchase. Used or rental books If you rent or purchase a used book with an access code, the access code may have been redeemed previously and you may have to purchase a new access code. Access codes Access codes that are purchased from sellers other than Pearson carry a higher risk of being either the wrong ISBN or a previously redeemed code. Check with the seller prior to purchase. -- Data Analysis with SPSS is designed to teach students how to explore data in a systematic manner using the most popular professional social statistics program on the market today. Written in ten manageable chapters, this book first introduces students to the approach researchers use to frame research questions and the logic of establishing causal relations. Students are then oriented to the SPSS program and how to examine data sets. Subsequent chapters guide them through univariate analysis, bivariate analysis, graphic analysis, and multivariate analysis. Students conclude their course by learning how to write a research report and by engaging in their own research project. Each book is packaged with a disk containing the GSS (General Social Survey) file and the States data files. The GSS file contains 100 variables generated from interviews with 2,900 people, concerning their behaviors and attitudes on a wide variety of issues such as abortion, religion, prejudice, sexuality, and politics. The States data allows comparison of all 50 states with 400 variables indicating issues such as unemployment, environment, criminality, population, and education. Students will ultimately use these data to conduct their own independent research project with SPSS. Note: MySearchLab does not come automatically packaged with this text. To purchase MySearchLab, please visit: www.mysearchlab.com or you can purchase a ValuePack of the text + MySearchLab with Pearson eText (at no additional cost). ValuePack ISBN-10: 0205863728 / ValuePack ISBN-13: 9780205863723

## Operations Research

*An Introduction*

**Author**: Hamdy A. Taha

**Publisher:**Pearson

**ISBN:**9780134444017

**Category:**Operations research

**Page:**848

**View:**4236

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"For junior/senior undergraduate and first-year graduate courses in Operations Research in departments of Industrial Engineering, Business Administration, Statistics, Computer Science, and Mathematics." "Operations Research" provides a broad focus on algorithmic and practical implementation of Operations Research (OR) techniques, using theory, applications, and computations to teach students OR basics. The book can be used conveniently in a survey course that encompasses all the major tools of operations research, or in two separate courses on deterministic and probabilistic decision-making. With the Tenth Edition, the author preserves classical algorithms by providing essential hand computational algorithms as an important part of OR history. Based on input and submissions from OR students, professors, and practitioners, the author also includes scenarios that show how classical algorithms can be beneficial in practice. These entries are included as "Aha! Moments" with each dealing with stories, anecdotes, and issues in OR theory, applications, computations, and teaching methodology that can advance the understanding of fundamental OR concepts. The Companion Website for "Operations Research, " 10/e (www.pearsonhighered.com/taha) provides valuable resources for both students and instructors. Resources include case studies that require students to employ OR tools from multiple chapters, Excel, TORA, and AMPL files as well as additional chapters and appendixes. A note about accessing the Companion Website: Instructors should click the Register link and follow the on-screen directions to access the site. Instructors need a Pearson Education account to register, but do not require an additional Access Code. Students can access the Companion Website by redeeming the Access Code included in the front of their new copy of "Operations Research, " 10/e. Students can also purchase Companion Website access online. The Instructor Resource Center contains the Solutions Manual and PowerPoints of the art from the book. Instructors can download these resources from www.pearsonhighered.com/irc"

## Introductory Statistics

**Author**: Neil A. Weiss

**Publisher:**Pearson College Division

**ISBN:**9780321691224

**Category:**Mathematics

**Page:**759

**View:**7143

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Weiss's Introductory Statistics, Ninth Edition is the ideal textbook for introductory statistics classes that emphasize statistical reasoning and critical thinking. The text is suitable for a one- or two-semester course. Comprehensive in its coverage, Weiss's meticulous style offers careful, detailed explanations to ease the learning process. With more than 1,000 data sets and more than 2,600 exercises, most using real data, this text takes a data-driven approach that encourages students to apply their knowledge and develop statistical literacy. Introductory Statistics, Ninth Edition, contains parallel presentation of critical-value and p-value approaches to hypothesis testing. This unique design allows both the flexibility to concentrate on one approach or the opportunity for greater depth in comparing the two. This edition continues the book's tradition of being on the cutting edge of statistical pedagogy, technology, and data analysis. It includes hundreds of new and updated exercises with real data from journals, magazines, newspapers, and websites. Datasets and other resources (where applicable) for this book are available here.

## An Introduction to Probability and Statistics

**Author**: Vijay K. Rohatgi,A.K. Md. Ehsanes Saleh

**Publisher:**John Wiley & Sons

**ISBN:**1118799658

**Category:**Mathematics

**Page:**728

**View:**3945

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A well-balanced introduction to probability theory and mathematical statistics Featuring updated material, An Introduction to Probability and Statistics, Third Edition remains a solid overview to probability theory and mathematical statistics. Divided intothree parts, the Third Edition begins by presenting the fundamentals and foundationsof probability. The second part addresses statistical inference, and the remainingchapters focus on special topics. An Introduction to Probability and Statistics, Third Edition includes: A new section on regression analysis to include multiple regression, logistic regression, and Poisson regression A reorganized chapter on large sample theory to emphasize the growing role of asymptotic statistics Additional topical coverage on bootstrapping, estimation procedures, and resampling Discussions on invariance, ancillary statistics, conjugate prior distributions, and invariant confidence intervals Over 550 problems and answers to most problems, as well as 350 worked out examples and 200 remarks Numerous figures to further illustrate examples and proofs throughout An Introduction to Probability and Statistics, Third Edition is an ideal reference and resource for scientists and engineers in the fields of statistics, mathematics, physics, industrial management, and engineering. The book is also an excellent text for upper-undergraduate and graduate-level students majoring in probability and statistics.

## Probability and Statistics for Computer Scientists, Second Edition

**Author**: Michael Baron

**Publisher:**CRC Press

**ISBN:**1498760600

**Category:**Mathematics

**Page:**449

**View:**7843

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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.

## Probability & Statistics for Engineers & Scientists, Global Edition

**Author**: N.A

**Publisher:**N.A

**ISBN:**9781292161365

**Category:**

**Page:**N.A

**View:**5099

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