Statistics

From a review of the first edition: "Modern Data Science with R... is rich with examples and is guided by a strong narrative voice. What's more, it presents an organizing framework that makes a convincing argument that data science is a course distinct...

Praise for the First Edition:". . . the book serves as an excellent tutorial on the R language, providing examples that illustrate programming concepts in the context of practical computational problems. The book will be of great interest for all...

At the intersection of computer science and healthcare, data analytics has emerged as a promising tool for solving problems across many healthcare-related disciplines. Supplying a comprehensive overview of recent healthcare analytics research, Healthcare...

Understanding Regression Analysis unifies diverse regression applications including the classical model, ANOVA models, generalized models including Poisson, Negative binomial, logistic, and survival, neural networks, and decision trees under a common...

This is a new edition of a very successful introduction to statistical methods for general insurance practitioners. No prior statistical knowledge is assumed, and the mathematical level required is approximately equivalent to school mathematics. Whilst...

Gain a clear understanding of the fundamental concepts and applications behind operations and supply chain management with the reader-friendly approach in Collier/Evans' popular OPERATIONS AND SUPPLY CHAIN MANAGEMENT, 2E. The authors present detailed,...

The richly illustrated Interactive Web-Based Data Visualization with R, plotly, and shiny focuses on the process of programming interactive web graphics for multidimensional data analysis. It is written for the data analyst who wants to leverage the...

Praise for previous editions:"Gandrud has written a great outline of how a fully reproducible research project should look from start to finish, with brief explanations of each tool that he uses along the way... Advanced undergraduate students in...

Textual Statistics with R comprehensively covers the main multidimensional methods in textual statistics supported by a specially-written package in R. Methods discussed include correspondence analysis, clustering, and multiple factor analysis for...

Gain a solid understanding of what is arguably the most critical and complex component of global supply chains with Novack/Gibson/Suzuki's TRANSPORTATION: A GLOBAL SUPPLY CHAIN PERSPECTIVE, 10E. You learn the fundamental role and importance of...

Mathematical Statistics: Basic Ideas and Selected Topics, Volume II presents important statistical concepts, methods, and tools not covered in the authors' previous volume. This second volume focuses on inference in non- and semiparametric models. It not...

In this provocative yet practical guidebook Steve Morlidge demonstrates why the approach and methods of performance reporting that all information professionals have been taught fails, and what we need to do differently to help us make sense of the...

Discover New Methods for Dealing with High-Dimensional DataA sparse statistical model has only a small number of nonzero parameters or weights; therefore, it is much easier to estimate and interpret than a dense model. Statistical Learning with Sparsity:...

The focus of this book is on the two major areas of risk theory: aggregate claims distributions and ruin theory. For aggregate claims distributions, detailed descriptions are given of recursive techniques that can be used in the individual and collective...

Using data from one season of NBA games, Basketball Data Science: With Applications in R is the perfect book for anyone interested in learning and applying data analytics in basketball. Whether assessing the spatial performance of an NBA player's shots...

This book concerns the use of concepts from statistical physics in the description of financial systems. The authors illustrate the scaling concepts used in probability theory, critical phenomena, and fully developed turbulent fluids. These concepts are...

Predictive modeling uses data to forecast future events. It exploits relationships between explanatory variables and the predicted variables from past occurrences to predict future outcomes. Forecasting financial events is a core skill that actuaries...

This book is a collection of applications of analytic techniques to a number of popular sports including baseball, basketball, hockey, Jai Alai, NFL football and horseracing. We focus on both the statistics of the sporting events and betting strategies...

Risk control and derivative pricing have become of major concern to financial institutions, and there is a real need for adequate statistical tools to measure and anticipate the amplitude of the potential moves of the financial markets. Summarising...

Find out why many businesses preferentially hire Six Sigma trained candidates. AN INTRODUCTION TO SIX SIGMA AND PROCESS IMPROVEMENT, 2e shows you the essence and basics of Six Sigma, as well as how Six Sigma has brought a renewed interest in the...

You don't have to be a mathematician to maximize the power of quantitative methods. Written for the current-or future-business professional, QUANTITATIVE METHODS FOR BUSINESS, 13E makes it easy for you to understand how you can most effectively use...

Data Science for Wind Energy provides an in-depth discussion on how data science methods can improve decision making for wind energy applications, near-ground wind field analysis and forecast, turbine power curve fitting and performance analysis, turbine...

At the intersection between statistical physics and rigorous econometric analysis, this powerful new framework sheds light on how innovation and competition shape the growth and decline of companies and industries. Analyzing various sources of data...

Research on the problem of clustering tends to be fragmented across the pattern recognition, database, data mining, and machine learning communities. Addressing this problem in a unified way, Data Clustering: Algorithms and Applications provides complete...

* Gives thorough consideration of the needs for environmental research in both spatial and temporal domains. * Features examples of applications involving field-collected data ranging from individual observations to data logging. * Includes examples also...

A guide to getting the crucial business case right?every time Showing professionals how to calculate the value of typical budgeting and funding requests quickly and easily, Making Technology Investments Profitable, Second Edition applies the "Value...

Focusing on what actuaries need in practice, this introductory account provides readers with essential tools for handling complex problems and explains how simulation models can be created, used and re-used (with modifications) in related situations. The...

Advanced Data Science and Analytics with Python enables data scientists to continue developing their skills and apply them in business as well as academic settings. The subjects discussed in this book are complementary and a follow-up to the topics...

Apologies but we at Booksplease don't have a full description for this book.Book InformationISBN 9781980914815Author Matt CoreyFormat PaperbackPage Count 204Imprint Independently PublishedPublisher Independently PublishedWeight(grams) 281gDimensions(mm)...

Bootstrapping is a conceptually simple statistical technique to increase the quality of estimates, conduct robustness checks and compute standard errors for virtually any statistic. This book provides an intelligible and compact introduction for...

"This book is a great way to both start learning data science through the promising Julia language and to become an efficient data scientist."- Professor Charles Bouveyron, INRIA Chair in Data Science, Universite Cote d'Azur, Nice, FranceJulia, an...

Sufficient dimension reduction is a rapidly developing research field that has wide applications in regression diagnostics, data visualization, machine learning, genomics, image processing, pattern recognition, and medicine, because they are fields that...

Practical Statistics is an introduction and reference guide for those studying business and management at postgraduate level, MBA students and professionals. It gives the reader a solid understanding of statistics without being too simple or...

Data Stewardship for Open Science: Implementing FAIR Principles has been written with the intention of making scientists, funders, and innovators in all disciplines and stages of their professional activities broadly aware of the need, complexity, and...

This book applies the mathematics and concepts of quantum mechanics and quantum field theory to the modelling of interest rates and the theory of options. Particular emphasis is placed on path integrals and Hamiltonians. Financial mathematics is...

Data Mining with R: Learning with Case Studies, Second Edition uses practical examples to illustrate the power of R and data mining. Providing an extensive update to the best-selling first edition, this new edition is divided into two parts. The first...

Are you innately curious about dynamically inter-operating financial markets? Since the crisis of 2008, there is a need for professionals with more understanding about statistics and data analysis, who can discuss the various risk metrics, particularly...

Praise for Linear Models with R:This book is a must-have tool for anyone interested in understanding and applying linear models. The logical ordering of the chapters is well thought out and portrays Faraway's wealth of experience in teaching and using...

Delivering cutting-edge coverage that includes the latest thinking and practices from the field, QUALITY AND PERFORMANCE EXCELLENCE, 8e presents the basic principles and tools associated with quality and performance excellence. Packed with relevant,...

This text provides a comprehensive overview of Data Science. With the continued advancement in storage and computing technologies, data science has emerged as one of the most desired fields in driving business decisions. Data science employs techniques...