Read Books Online and Download eBooks, EPub, PDF, Mobi, Kindle, Text Full Free.
Probability And Data
Download Probability And Data full books in PDF, epub, and Kindle. Read online Probability And Data ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
Book Synopsis Probability and Statistics for Data Science by : Norman Matloff
Download or read book Probability and Statistics for Data Science written by Norman Matloff and published by CRC Press. This book was released on 2019-06-21 with total page 295 pages. Available in PDF, EPUB and Kindle. Book excerpt: Probability and Statistics for Data Science: Math + R + Data covers "math stat"—distributions, expected value, estimation etc.—but takes the phrase "Data Science" in the title quite seriously: * Real datasets are used extensively. * All data analysis is supported by R coding. * Includes many Data Science applications, such as PCA, mixture distributions, random graph models, Hidden Markov models, linear and logistic regression, and neural networks. * Leads the student to think critically about the "how" and "why" of statistics, and to "see the big picture." * Not "theorem/proof"-oriented, but concepts and models are stated in a mathematically precise manner. Prerequisites are calculus, some matrix algebra, and some experience in programming. Norman Matloff is a professor of computer science at the University of California, Davis, and was formerly a statistics professor there. He is on the editorial boards of the Journal of Statistical Software and The R Journal. His book Statistical Regression and Classification: From Linear Models to Machine Learning was the recipient of the Ziegel Award for the best book reviewed in Technometrics in 2017. He is a recipient of his university's Distinguished Teaching Award.
Book Synopsis Introduction to Probability for Data Science by : Stanley H. Chan
Download or read book Introduction to Probability for Data Science written by Stanley H. Chan and published by Michigan Publishing Services. This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Probability is one of the most interesting subjects in electrical engineering and computer science. It bridges our favorite engineering principles to the practical reality, a world that is full of uncertainty. However, because probability is such a mature subject, the undergraduate textbooks alone might fill several rows of shelves in a library. When the literature is so rich, the challenge becomes how one can pierce through to the insight while diving into the details. For example, many of you have used a normal random variable before, but have you ever wondered where the 'bell shape' comes from? Every probability class will teach you about flipping a coin, but how can 'flipping a coin' ever be useful in machine learning today? Data scientists use the Poisson random variables to model the internet traffic, but where does the gorgeous Poisson equation come from? This book is designed to fill these gaps with knowledge that is essential to all data science students." -- Preface.
Book Synopsis Probability, Statistics, and Data by : Darrin Speegle
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.
Book Synopsis High-Dimensional Probability by : Roman Vershynin
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.
Book Synopsis Probability, Statistics, and Truth by : Richard Von Mises
Download or read book Probability, Statistics, and Truth written by Richard Von Mises and published by Courier Corporation. This book was released on 1981-01-01 with total page 273 pages. Available in PDF, EPUB and Kindle. Book excerpt: This comprehensive study of probability considers the approaches of Pascal, Laplace, Poisson, and others. It also discusses Laws of Large Numbers, the theory of errors, and other relevant topics.
Book Synopsis A Modern Introduction to Probability and Statistics by : F.M. Dekking
Download or read book A Modern Introduction to Probability and Statistics written by F.M. Dekking and published by Springer Science & Business Media. This book was released on 2006-03-30 with total page 485 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Book Synopsis Understanding Probability and Statistics by : Ruma Falk
Download or read book Understanding Probability and Statistics written by Ruma Falk and published by A K Peters/CRC Press. This book was released on 1993-04-15 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Probability and Statistics by : Ronald Deep
Download or read book Probability and Statistics written by Ronald Deep and published by Elsevier. This book was released on 2005-10-25 with total page 707 pages. Available in PDF, EPUB and Kindle. Book excerpt: Probability and Statistics is a calculus-based treatment of probability concurrent with and integrated with statistics. * Incorporates more than 1,000 engaging problems with answers* Includes more than 300 solved examples* Uses varied problem solving methods
Book Synopsis Probability and Statistics by : Michael J. Evans
Download or read book Probability and Statistics written by Michael J. Evans and published by Macmillan. This book was released on 2004 with total page 704 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unlike traditional introductory math/stat textbooks, Probability and Statistics: The Science of Uncertainty brings a modern flavor based on incorporating the computer to the course and an integrated approach to inference. From the start the book integrates simulations into its theoretical coverage, and emphasizes the use of computer-powered computation throughout.* Math and science majors with just one year of calculus can use this text and experience a refreshing blend of applications and theory that goes beyond merely mastering the technicalities. They'll get a thorough grounding in probability theory, and go beyond that to the theory of statistical inference and its applications. An integrated approach to inference is presented that includes the frequency approach as well as Bayesian methodology. Bayesian inference is developed as a logical extension of likelihood methods. A separate chapter is devoted to the important topic of model checking and this is applied in the context of the standard applied statistical techniques. Examples of data analyses using real-world data are presented throughout the text. A final chapter introduces a number of the most important stochastic process models using elementary methods. *Note: An appendix in the book contains Minitab code for more involved computations. The code can be used by students as templates for their own calculations. If a software package like Minitab is used with the course then no programming is required by the students.
Book Synopsis Probability for Data Scientists (First Edition) by : Juana Sánchez
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 Probability written by Guy Lebanon and published by . This book was released on 2012-10-09 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction to probability theory with an emphasis on the multivariate case. Includes random vectors, random processes, Markov chains, limit theorems, and related mathematics such as metric spaces, measure theory, and integration.
Book Synopsis A Probability and Statistics Companion by : John J. Kinney
Download or read book A Probability and Statistics Companion written by John J. Kinney and published by John Wiley & Sons. This book was released on 2009-05-06 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: An accessible and engaging introduction to the study of probability and statistics Utilizing entertaining real-world examples, A Probability and Statistics Companion provides aunique, interesting, and accessible introduction to probability and statistics. This one-of-a-kind book delves into practical topics that are crucial in the analysis of sample surveys and experimentation. This handy book contains introductory explanations of the major topics in probability and statistics, including hypothesis testing and regression, while also delving into more advanced topics such as the analysis of sample surveys, analysis of experimental data, and statistical process control. The book recognizes that there are many sampling techniques that can actually improve on simple random sampling, and in addition, an introduction to the design of experiments is provided to reflect recent advances in conducting scientific experiments. This blend of coverage results in the development of a deeper understanding and solid foundation for the study of probability and statistics. Additional topical coverage includes: Probability and sample spaces Choosing the best candidate Acceptance sampling Conditional probability Random variables and discrete probability distributions Waiting time problems Continuous probability distributions Statistical inference Nonparametric methods Least squares and medians Recursions and probability Each chapter contains exercises and explorations for readers who wish to conduct independent projects or investigations. The discussion of most methods is complemented with applications to engaging, real-world scenarios such as winning speeds at the Indianapolis 500 and predicting winners of the World Series. In addition, the book enhances the visual nature of the subject with numerous multidimensional graphical representations of the presented examples. A Probability and Statistics Companion is an excellent book for introductory probability and statistics courses at the undergraduate level. It is also a valuable reference for professionals who use statistical concepts to make informed decisions in their day-to-day work.
Book Synopsis Elements of Probability and Statistics by : Francesca Biagini
Download or read book Elements of Probability and Statistics written by Francesca Biagini and published by Springer. This book was released on 2016-01-22 with total page 246 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an introduction to elementary probability and to Bayesian statistics using de Finetti's subjectivist approach. One of the features of this approach is that it does not require the introduction of sample space – a non-intrinsic concept that makes the treatment of elementary probability unnecessarily complicate – but introduces as fundamental the concept of random numbers directly related to their interpretation in applications. Events become a particular case of random numbers and probability a particular case of expectation when it is applied to events. The subjective evaluation of expectation and of conditional expectation is based on an economic choice of an acceptable bet or penalty. The properties of expectation and conditional expectation are derived by applying a coherence criterion that the evaluation has to follow. The book is suitable for all introductory courses in probability and statistics for students in Mathematics, Informatics, Engineering, and Physics.
Book Synopsis Probability and Statistical Inference by : Robert Bartoszynski
Download or read book Probability and Statistical Inference written by Robert Bartoszynski and published by John Wiley & Sons. This book was released on 2007-11-16 with total page 672 pages. Available in PDF, EPUB and Kindle. Book excerpt: Now updated in a valuable new edition—this user-friendly book focuses on understanding the "why" of mathematical statistics Probability and Statistical Inference, Second Edition introduces key probability and statis-tical concepts through non-trivial, real-world examples and promotes the developmentof intuition rather than simple application. With its coverage of the recent advancements in computer-intensive methods, this update successfully provides the comp-rehensive tools needed to develop a broad understanding of the theory of statisticsand its probabilistic foundations. This outstanding new edition continues to encouragereaders to recognize and fully understand the why, not just the how, behind the concepts,theorems, and methods of statistics. Clear explanations are presented and appliedto various examples that help to impart a deeper understanding of theorems and methods—from fundamental statistical concepts to computational details. Additional features of this Second Edition include: A new chapter on random samples Coverage of computer-intensive techniques in statistical inference featuring Monte Carlo and resampling methods, such as bootstrap and permutation tests, bootstrap confidence intervals with supporting R codes, and additional examples available via the book's FTP site Treatment of survival and hazard function, methods of obtaining estimators, and Bayes estimating Real-world examples that illuminate presented concepts Exercises at the end of each section Providing a straightforward, contemporary approach to modern-day statistical applications, Probability and Statistical Inference, Second Edition is an ideal text for advanced undergraduate- and graduate-level courses in probability and statistical inference. It also serves as a valuable reference for practitioners in any discipline who wish to gain further insight into the latest statistical tools.
Book Synopsis Probability, Random Variables, and Data Analytics with Engineering Applications by : P. Mohana Shankar
Download or read book Probability, Random Variables, and Data Analytics with Engineering Applications written by P. Mohana Shankar and published by Springer Nature. This book was released on 2021-02-08 with total page 481 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book bridges the gap between theory and applications that currently exist in undergraduate engineering probability textbooks. It offers examples and exercises using data (sets) in addition to traditional analytical and conceptual ones. Conceptual topics such as one and two random variables, transformations, etc. are presented with a focus on applications. Data analytics related portions of the book offer detailed coverage of receiver operating characteristics curves, parametric and nonparametric hypothesis testing, bootstrapping, performance analysis of machine vision and clinical diagnostic systems, and so on. With Excel spreadsheets of data provided, the book offers a balanced mix of traditional topics and data analytics expanding the scope, diversity, and applications of engineering probability. This makes the contents of the book relevant to current and future applications students are likely to encounter in their endeavors after completion of their studies. A full suite of classroom material is included. A solutions manual is available for instructors. Bridges the gap between conceptual topics and data analytics through appropriate examples and exercises; Features 100's of exercises comprising of traditional analytical ones and others based on data sets relevant to machine vision, machine learning and medical diagnostics; Intersperses analytical approaches with computational ones, providing two-level verifications of a majority of examples and exercises.
Book Synopsis Everyday Probability and Statistics by : M. M. Woolfson
Download or read book Everyday Probability and Statistics written by M. M. Woolfson and published by Imperial College Press. This book was released on 2008 with total page 234 pages. Available in PDF, EPUB and Kindle. Book excerpt: Probability and statistics impinge on the life of the average person in a variety of ways OCo as is suggested by the title of this book. Very often, information is provided that is factually accurate but intended to present a biased view. This book presents the important results of probability and statistics without making heavy mathematical demands on the reader. It should enable an intelligent reader to properly assess statistical information and to understand that the same information can be presented in different ways.
Book Synopsis Probability and Statistics for Economists by : Bruce Hansen
Download or read book Probability and Statistics for Economists written by Bruce Hansen and published by Princeton University Press. This book was released on 2022-06-28 with total page 417 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive and up-to-date introduction to the mathematics that all economics students need to know Probability theory is the quantitative language used to handle uncertainty and is the foundation of modern statistics. Probability and Statistics for Economists provides graduate and PhD students with an essential introduction to mathematical probability and statistical theory, which are the basis of the methods used in econometrics. This incisive textbook teaches fundamental concepts, emphasizes modern, real-world applications, and gives students an intuitive understanding of the mathematics that every economist needs to know. Covers probability and statistics with mathematical rigor while emphasizing intuitive explanations that are accessible to economics students of all backgrounds Discusses random variables, parametric and multivariate distributions, sampling, the law of large numbers, central limit theory, maximum likelihood estimation, numerical optimization, hypothesis testing, and more Features hundreds of exercises that enable students to learn by doing Includes an in-depth appendix summarizing important mathematical results as well as a wealth of real-world examples Can serve as a core textbook for a first-semester PhD course in econometrics and as a companion book to Bruce E. Hansen’s Econometrics Also an invaluable reference for researchers and practitioners
