1# Library to Find Best eBook for Read
Author : Peter M. Aronow
Release : 2019-01-31
Genre : Mathematics
Kind : eBook
Book Rating : 916/5 ( reviews)
Book Synopsis Foundations of Agnostic Statistics by : Peter M. Aronow
Download or read book Foundations of Agnostic Statistics written by Peter M. Aronow. This book was released on 2019-01-31. Available in PDF, EPUB and Kindle. Book excerpt: Provides an introduction to modern statistical theory for social and health scientists while invoking minimal modeling assumptions.
Author : D.G. Rees
Release : 1987-09-01
Genre : Mathematics
Kind : eBook
Book Rating : 608/5 ( reviews)
Book Synopsis Foundations of Statistics by : D.G. Rees
Download or read book Foundations of Statistics written by D.G. Rees. This book was released on 1987-09-01. Available in PDF, EPUB and Kindle. Book excerpt: This text provides a through, straightforward first course on basics statistics. Emphasizing the application of theory, it contains 200 fully worked examples and supplies exercises in each chapter-complete with hints and answers.
Author : Avrim Blum
Release : 2020-01-23
Genre : Computers
Kind : eBook
Book Rating : 360/5 ( reviews)
Book Synopsis Foundations of Data Science by : Avrim Blum
Download or read book Foundations of Data Science written by Avrim Blum. This book was released on 2020-01-23. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an introduction to the mathematical and algorithmic foundations of data science, including machine learning, high-dimensional geometry, and analysis of large networks. Topics include the counterintuitive nature of data in high dimensions, important linear algebraic techniques such as singular value decomposition, the theory of random walks and Markov chains, the fundamentals of and important algorithms for machine learning, algorithms and analysis for clustering, probabilistic models for large networks, representation learning including topic modelling and non-negative matrix factorization, wavelets and compressed sensing. Important probabilistic techniques are developed including the law of large numbers, tail inequalities, analysis of random projections, generalization guarantees in machine learning, and moment methods for analysis of phase transitions in large random graphs. Additionally, important structural and complexity measures are discussed such as matrix norms and VC-dimension. This book is suitable for both undergraduate and graduate courses in the design and analysis of algorithms for data.
Author : Jay L. Devore
Release : 2021-04-29
Genre : Mathematics
Kind : eBook
Book Rating : 563/5 ( reviews)
Book Synopsis Modern Mathematical Statistics with Applications by : Jay L. Devore
Download or read book Modern Mathematical Statistics with Applications written by Jay L. Devore. This book was released on 2021-04-29. Available in PDF, EPUB and Kindle. Book excerpt: This 3rd edition of Modern Mathematical Statistics with Applications tries to strike a balance between mathematical foundations and statistical practice. The book provides a clear and current exposition of statistical concepts and methodology, including many examples and exercises based on real data gleaned from publicly available sources. Here is a small but representative selection of scenarios for our examples and exercises based on information in recent articles: Use of the “Big Mac index” by the publication The Economist as a humorous way to compare product costs across nations Visualizing how the concentration of lead levels in cartridges varies for each of five brands of e-cigarettes Describing the distribution of grip size among surgeons and how it impacts their ability to use a particular brand of surgical stapler Estimating the true average odometer reading of used Porsche Boxsters listed for sale on www.cars.com Comparing head acceleration after impact when wearing a football helmet with acceleration without a helmet Investigating the relationship between body mass index and foot load while running The main focus of the book is on presenting and illustrating methods of inferential statistics used by investigators in a wide variety of disciplines, from actuarial science all the way to zoology. It begins with a chapter on descriptive statistics that immediately exposes the reader to the analysis of real data. The next six chapters develop the probability material that facilitates the transition from simply describing data to drawing formal conclusions based on inferential methodology. Point estimation, the use of statistical intervals, and hypothesis testing are the topics of the first three inferential chapters. The remainder of the book explores the use of these methods in a variety of more complex settings. This edition includes many new examples and exercises as well as an introduction to the simulation of events and probability distributions. There are more than 1300 exercises in the book, ranging from very straightforward to reasonably challenging. Many sections have been rewritten with the goal of streamlining and providing a more accessible exposition. Output from the most common statistical software packages is included wherever appropriate (a feature absent from virtually all other mathematical statistics textbooks). The authors hope that their enthusiasm for the theory and applicability of statistics to real world problems will encourage students to pursue more training in the discipline.
Author : Rick Durrett
Release : 2009-07-31
Genre : Mathematics
Kind : eBook
Book Rating : 731/5 ( reviews)
Book Synopsis Elementary Probability for Applications by : Rick Durrett
Download or read book Elementary Probability for Applications written by Rick Durrett. This book was released on 2009-07-31. Available in PDF, EPUB and Kindle. Book excerpt: This clear and lively introduction to probability theory concentrates on the results that are the most useful for applications, including combinatorial probability and Markov chains. Concise and focused, it is designed for a one-semester introductory course in probability for students who have some familiarity with basic calculus. Reflecting the author's philosophy that the best way to learn probability is to see it in action, there are more than 350 problems and 200 examples. The examples contain all the old standards such as the birthday problem and Monty Hall, but also include a number of applications not found in other books, from areas as broad ranging as genetics, sports, finance, and inventory management.
