Filename: a-modern-introduction-to-probability-and-statistics.pdf
ISBN: 9781846281686
Release Date: 2006-03-30
Number of pages: 488
Author: F.M. Dekking
Publisher: Springer Science & Business Media

Download and read online A Modern Introduction to Probability and Statistics in PDF and EPUB Suitable for self study Use real examples and real data sets that will be familiar to the audience Introduction to the bootstrap is included – this is a modern method missing in many other books

Filename: a-modern-introduction-to-probability-and-statistics.pdf
ISBN: 9781852338961
Release Date: 2005-01-01
Number of pages: 486
Author: F.M. Dekking
Publisher: Springer Science & Business Media

Download and read online A Modern Introduction to Probability and Statistics in PDF and EPUB Probability and Statistics are studied by most science students. Many current texts in the area are just cookbooks and, as a result, students do not know why they perform the methods they are taught, or why the methods work. This book readdresses these shortcomings; by using examples, often from real-life and using real data, the authors show how the fundamentals of probabilistic and statistical theories arise intuitively. There are numerous quick exercises to give direct feedback to students, and over 350 exercises, half of which have answers, of which half have full solutions. A website gives access to the data files used in the text, and, for instructors, the remaining solutions. The only prerequisite is a first course in calculus.

Filename: a-modern-introduction-to-probability-and-statistics.pdf
ISBN: 9781467251822
Release Date: 2016-10-17
Number of pages: 43
Author: CTI Reviews
Publisher: Cram101 Textbook Reviews

Download and read online A Modern Introduction To Probability And Statistics in PDF and EPUB Facts101 is your complete guide to A Modern Introduction To Probability And Statistics. In this book, you will learn topics such as as those in your book plus much more. With key features such as key terms, people and places, Facts101 gives you all the information you need to prepare for your next exam. Our practice tests are specific to the textbook and we have designed tools to make the most of your limited study time.

Filename: introduction-to-probability-and-statistics.pdf
ISBN: 9781133103752
Release Date: 2012-01-01
Number of pages: 744
Author: William Mendenhall
Publisher: Cengage Learning

Download and read online Introduction to Probability and Statistics in PDF and EPUB Used by hundreds of thousands of students since its first edition, INTRODUCTION TO PROBABILITY AND STATISTICS, Fourteenth Edition, continues to blend the best of its proven, error-free coverage with new innovations. Written for the higher end of the traditional introductory statistics market, the book takes advantage of modern technology--including computational software and interactive visual tools--to facilitate statistical reasoning as well as the interpretation of statistical results. In addition to showing how to apply statistical procedures, the authors explain how to describe real sets of data meaningfully, what the statistical tests mean in terms of their practical applications, how to evaluate the validity of the assumptions behind statistical tests, and what to do when statistical assumptions have been violated. The new edition retains the statistical integrity, examples, exercises, and exposition that have made this text a market leader--and builds upon this tradition of excellence with new technology integration. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.

Filename: introduction-to-probability.pdf
ISBN: 9781466575592
Release Date: 2014-07-24
Number of pages: 596
Author: Joseph K. Blitzstein
Publisher: CRC Press

Download and read online Introduction to Probability in PDF and EPUB Developed from celebrated Harvard statistics lectures, Introduction to Probability provides essential language and tools for understanding statistics, randomness, and uncertainty. The book explores a wide variety of applications and examples, ranging from coincidences and paradoxes to Google PageRank and Markov chain Monte Carlo (MCMC). Additional application areas explored include genetics, medicine, computer science, and information theory. The print book version includes a code that provides free access to an eBook version. The authors present the material in an accessible style and motivate concepts using real-world examples. Throughout, they use stories to uncover connections between the fundamental distributions in statistics and conditioning to reduce complicated problems to manageable pieces. The book includes many intuitive explanations, diagrams, and practice problems. Each chapter ends with a section showing how to perform relevant simulations and calculations in R, a free statistical software environment.

Filename: modern-mathematical-statistics-with-applications.pdf
ISBN: 9781461403913
Release Date: 2011-12-07
Number of pages: 845
Author: Jay L. Devore
Publisher: Springer Science & Business Media

Download and read online Modern Mathematical Statistics with Applications in PDF and EPUB Modern Mathematical Statistics with Applications, Second Edition strikes a balance between mathematical foundations and statistical practice. In keeping with the recommendation that every math student should study statistics and probability with an emphasis on data analysis, accomplished authors Jay Devore and Kenneth Berk make statistical concepts and methods clear and relevant through careful explanations and a broad range of applications involving real data. The main focus of the book is on presenting and illustrating methods of inferential statistics that are useful in research. It begins with a chapter on descriptive statistics that immediately exposes the reader to real data. The next six chapters develop the probability material that bridges the gap between descriptive and inferential statistics. Point estimation, inferences based on statistical intervals, and hypothesis testing are then introduced in the next three chapters. The remainder of the book explores the use of this methodology in a variety of more complex settings. This edition includes a plethora of new exercises, a number of which are similar to what would be encountered on the actuarial exams that cover probability and statistics. Representative applications include investigating whether the average tip percentage in a particular restaurant exceeds the standard 15%, considering whether the flavor and aroma of Champagne are affected by bottle temperature or type of pour, modeling the relationship between college graduation rate and average SAT score, and assessing the likelihood of O-ring failure in space shuttle launches as related to launch temperature.

Filename: introduction-to-probability-with-r.pdf
ISBN: 142006522X
Release Date: 2008-01-24
Number of pages: 384
Author: Kenneth Baclawski
Publisher: CRC Press

Download and read online Introduction to Probability with R in PDF and EPUB Based on a popular course taught by the late Gian-Carlo Rota of MIT, with many new topics covered as well, Introduction to Probability with R presents R programs and animations to provide an intuitive yet rigorous understanding of how to model natural phenomena from a probabilistic point of view. Although the R programs are small in length, they are just as sophisticated and powerful as longer programs in other languages. This brevity makes it easy for students to become proficient in R. This calculus-based introduction organizes the material around key themes. One of the most important themes centers on viewing probability as a way to look at the world, helping students think and reason probabilistically. The text also shows how to combine and link stochastic processes to form more complex processes that are better models of natural phenomena. In addition, it presents a unified treatment of transforms, such as Laplace, Fourier, and z; the foundations of fundamental stochastic processes using entropy and information; and an introduction to Markov chains from various viewpoints. Each chapter includes a short biographical note about a contributor to probability theory, exercises, and selected answers. The book has an accompanying website with more information.

Filename: introduction-to-probability-and-mathematical-statistics.pdf
ISBN: 0534380204
Release Date: 2000-03-01
Number of pages: 644
Author: Lee J. Bain
Publisher: Duxbury Press

Download and read online Introduction to Probability and Mathematical Statistics in PDF and EPUB The Second Edition of INTRODUCTION TO PROBABILITY AND MATHEMATICAL STATISTICS focuses on developing the skills to build probability (stochastic) models. Lee J. Bain and Max Engelhardt focus on the mathematical development of the subject, with examples and exercises oriented toward applications.

Filename: random-walk-a-modern-introduction.pdf
ISBN: 9781139488761
Release Date: 2010-06-24
Number of pages:
Author: Gregory F. Lawler
Publisher: Cambridge University Press

Download and read online Random Walk A Modern Introduction in PDF and EPUB Random walks are stochastic processes formed by successive summation of independent, identically distributed random variables and are one of the most studied topics in probability theory. This contemporary introduction evolved from courses taught at Cornell University and the University of Chicago by the first author, who is one of the most highly regarded researchers in the field of stochastic processes. This text meets the need for a modern reference to the detailed properties of an important class of random walks on the integer lattice. It is suitable for probabilists, mathematicians working in related fields, and for researchers in other disciplines who use random walks in modeling.

Filename: introduction-to-probability.pdf
ISBN: 0821807498
Release Date: 1997-01-01
Number of pages: 510
Author: Charles Miller Grinstead
Publisher: American Mathematical Soc.

Download and read online Introduction to Probability in PDF and EPUB This text is designed for an introductory probability course at the university level for undergraduates in mathematics, the physical and social sciences, engineering, and computer science. It presents a thorough treatment of probability ideas and techniques necessary for a firm understanding of the subject.

Filename: probability-with-statistical-applications.pdf
ISBN: 9780817682507
Release Date: 2011-12-16
Number of pages: 347
Author: Rinaldo B. Schinazi
Publisher: Springer Science & Business Media

Download and read online Probability with Statistical Applications in PDF and EPUB This second edition textbook offers a practical introduction to probability for undergraduates at all levels with different backgrounds and views towards applications. Calculus is a prerequisite for understanding the basic concepts, however the book is written with a sensitivity to students’ common difficulties with calculus that does not obscure the thorough treatment of the probability content. The first six chapters of this text neatly and concisely cover the material traditionally required by most undergraduate programs for a first course in probability. The comprehensive text includes a multitude of new examples and exercises, and careful revisions throughout. Particular attention is given to the expansion of the last three chapters of the book with the addition of one entirely new chapter (9) on ’Finding and Comparing Estimators.’ The classroom-tested material presented in this second edition forms the basis for a second course introducing mathematical statistics.

Filename: introduction-to-probability-and-statistics-using-r.pdf
ISBN: 9780557249794
Release Date:
Number of pages:
Author: G. Jay Kerns
Publisher: Lulu.com

Download and read online Introduction to Probability and Statistics Using R in PDF and EPUB

Filename: probability-and-statistics-with-r.pdf
ISBN: 9781584888925
Release Date: 2008-04-11
Number of pages: 726
Author: Maria Dolores Ugarte
Publisher: CRC Press

Download and read online Probability and Statistics with R in PDF and EPUB Designed for an intermediate undergraduate course, Probability and Statistics with R shows students how to solve various statistical problems using both parametric and nonparametric techniques via the open source software R. It provides numerous real-world examples, carefully explained proofs, end-of-chapter problems, and illuminating graphs to facilitate hands-on learning. Integrating theory with practice, the text briefly introduces the syntax, structures, and functions of the S language, before covering important graphically and numerically descriptive methods. The next several chapters elucidate probability and random variables topics, including univariate and multivariate distributions. After exploring sampling distributions, the authors discuss point estimation, confidence intervals, hypothesis testing, and a wide range of nonparametric methods. With a focus on experimental design, the book also presents fixed- and random-effects models as well as randomized block and two-factor factorial designs. The final chapter describes simple and multiple regression analyses. Demonstrating that R can be used as a powerful teaching aid, this comprehensive text presents extensive treatments of data analysis using parametric and nonparametric techniques. It effectively links statistical concepts with R procedures, enabling the application of the language to the vast world of statistics.

Filename: grinstead-and-snell-s-introduction-to-probability.pdf
ISBN: 161610046X
Release Date: 2009-09-01
Number of pages: 510
Author: Charles M. Grinstead
Publisher: Orange Grove Text Plus

Download and read online Grinstead and Snell s Introduction to Probability in PDF and EPUB

Filename: a-natural-introduction-to-probability-theory.pdf
ISBN: 3764387246
Release Date: 2008-03-16
Number of pages: 198
Author: R. Meester
Publisher: Springer Science & Business Media

Download and read online A Natural Introduction to Probability Theory in PDF and EPUB Compactly written, but nevertheless very readable, appealing to intuition, this introduction to probability theory is an excellent textbook for a one-semester course for undergraduates in any direction that uses probabilistic ideas. Technical machinery is only introduced when necessary. The route is rigorous but does not use measure theory. The text is illustrated with many original and surprising examples and problems taken from classical applications like gambling, geometry or graph theory, as well as from applications in biology, medicine, social sciences, sports, and coding theory. Only first-year calculus is required.