Sports Analytics in Practice with R

A reliable, cost-effective approach to extracting priceless business information from all sources of text Excavating actionable business insights from data is a complex undertaking, and that complexity is magnified by an order of magnitude when the focus is on documents and other text information. This book takes a practical, hands-on approach to teaching you a reliable, cost-effective approach to mining the vast, untold riches buried within all forms of text using R. Author Ted Kwartler clearly describes all of the tools needed to perform text mining and shows you how to use them to identify practical business applications to get your creative text mining efforts started right away. With the help of numerous real-world examples and case studies from industries ranging from healthcare to entertainment to telecommunications, he demonstrates how to execute an array of text mining processes and functions, including sentiment scoring, topic modelling, predictive modelling, extracting clickbait from headlines, and more. You’ll learn how to: Identify actionable social media posts to improve customer service Use text mining in HR to identify candidate perceptions of an organisation, match job descriptions with resumes, and more Extract priceless information from virtually all digital and print sources, including the news media, social media sites, PDFs, and even JPEG and GIF image files Make text mining an integral component of marketing in order to identify brand evangelists, impact customer propensity modelling, and much more Most companies’ data mining efforts focus almost exclusively on numerical and categorical data, while text remains a largely untapped resource. Especially in a global marketplace where being first to identify and respond to customer needs and expectations imparts an unbeatable competitive advantage, text represents a source of immense potential value. Unfortunately, there is no reliable, cost-effective technology for extracting analytical insights from the huge and ever-growing volume of text available online and other digital sources, as well as from paper documents—until now.

Collecting, analyzing, and extracting valuable information from a large amount of data requires easily accessible, robust, computational and analytical tools. Data Mining and Business Analytics with R utilizes the open source software R for the analysis, exploration, and simplification of large high-dimensional data sets. As a result, readers are provided with the needed guidance to model and interpret complicated data and become adept at building powerful models for prediction and classification. Highlighting both underlying concepts and practical computational skills, Data Mining and Business Analytics with R begins with coverage of standard linear regression and the importance of parsimony in statistical modeling. The book includes important topics such as penalty-based variable selection (LASSO); logistic regression; regression and classification trees; clustering; principal components and partial least squares; and the analysis of text and network data. In addition, the book presents: • A thorough discussion and extensive demonstration of the theory behind the most useful data mining tools • Illustrations of how to use the outlined concepts in real-world situations • Readily available additional data sets and related R code allowing readers to apply their own analyses to the discussed materials • Numerous exercises to help readers with computing skills and deepen their understanding of the material Data Mining and Business Analytics with R is an excellent graduate-level textbook for courses on data mining and business analytics. The book is also a valuable reference for practitioners who collect and analyze data in the fields of finance, operations management, marketing, and the information sciences.

AVOID THE MISTAKES THAT OTHERS MAKE – LEARN WHAT LEADS TO BEST PRACTICE AND KICKSTART SUCCESS This groundbreaking resource provides comprehensive coverage across all aspects of business analytics, presenting proven management guidelines to drive sustainable differentiation. Through a rich set of case studies, author Evan Stubbs reviews solutions and examples to over twenty common problems spanning managing analytics assets and information, leveraging technology, nurturing skills, and defining processes. Delivering Business Analytics also outlines the Data Scientist’s Code, fifteen principles that when followed ensure constant movement towards effective practice. Practical advice is offered for addressing various analytics issues; the advantages and disadvantages of each issue’s solution; and how these solutions can optimally create organizational value. With an emphasis on real-world examples and pragmatic advice throughout, Delivering Business Analytics provides a reference guide on: The economic principles behind how business analytics leads to competitive differentiation The elements which define best practice The Data Scientist’s Code, fifteen management principles that when followed help teams move towards best practice Practical solutions and frequent missteps to twenty-four common problems across people and process, systems and assets, and data and decision-making Drawing on the successes and failures of countless organizations, author Evan Stubbs provides a densely packed practical reference on how to increase the odds of success in designing business analytics systems and managing teams of data scientists. Uncover what constitutes best practice in business analytics and start achieving it with Delivering Business Analytics.

Sports Dentistry: Principles and Practice is a comprehensive resource that addresses all aspects of this burgeoning field of dentistry. Provides a comprehensive manual that covers the fundamental principles and practice of sports dentistry Addresses all aspects of sports dentistry, including treatment of injuries, preventative measures, oral health and marketing and practice management Offers information on providing dental facilities at sporting arenas Presents suggestions for treating young children and the specific issues they present Includes a companion website with illustrative case studies

A complete guide to investing in and managing a portfolio of mortgage- and asset-backed securities Mortgage- and asset-backed securities are not as complex as they might seem. In fact, all of the information, financial models, and software needed to successfully invest in and manage a portfolio of these securities are available to the investment professional through open source software. Investing in Mortgage and Asset-Backed Securities + Website shows you how to achieve this goal. The book draws entirely on publicly available data and open source software to construct a complete analytic framework for investing in these securities. The analytic models used throughout the book either exist in the quantlib library, as an R package, or are programmed in R and incorporated into the analytic framework used. Examines the valuation of fixed-income securities—metrics, valuation framework, and return analysis Covers residential mortgage-backed securities—security cash flow, mortgage dollar roll, adjustable rate mortgages, and private label MBS Discusses prepayment modeling and the valuation of mortgage credit Presents mortgage-backed securities valuation techniques—pass-through valuation and interest rate models Engaging and informative, this book skillfully shows you how to build, rather than buy, models and proprietary analytical platforms that will allow you to invest in mortgage- and asset-backed securities.

Coaching Brain in Mind Foundations for Practice David Rock and Linda J. Page, PhD Discover the science behind brain-based coaching By understanding how the brain works, coaching professionals can better tailor their language, strategies, and goals to be in alignment with an individual's «hard-wired» way of thinking. Written by two well-known coaching professionals, David Rock and Linda Page, Coaching with the Brain in Mind presents the tools and methodologies that can be employed by novice and experienced coaches alike to create an effective—and ultimately more rewarding—relationship for both coach and client. This informative guide to the neuroscience of coaching clearly demonstrates how brain-based coaching works in practice, and how the power of the mind can be harnessed to help an individual learn and grow. Illustrated with numerous case examples and stories, this book is organized for immediate use by professionals in their client work. Coverage includes: A succinct but comprehensive overview of the major scientific and theoretical foundations for coaching and their implications for practice How the language of coaching—setting goals, making connections, becoming more aware, seeking breakthroughs, and taking action—parallels what neuroscientists tell us about how the brain operates Neuroscience as a natural platform for the ongoing development of coaching Building on the existing foundation of coaching by adding neuroscience as an evidence base for the profession, Coaching with the Brain in Mind shows that it is possible to become a better professional coach by understanding how the brain works. As well, the authors, through their research, present that an understanding of neuroscience research, however new and speculative, can help coaches and leaders fulfill their potential as change agents in the lives of others.

A must-have resource for educational professionals implementing Response to Intervention (RTI) programs in their schools RTI in Practice: A Practical Guide to Implementing Effective Evidence-Based Interventions in Your School is an innovative and timely guide that presents concrete, balanced perspectives and directions for implementing an effective RTI model in your school. Built upon the three tiers of effective general education and universal screening, targeted interventions, and intensive interventions, this authoritative resource addresses: Effective academic programs for all students How to use data to make decisions in general education Guidelines for setting goals, monitoring progress, and graphing intervention outcomes Multicultural considerations Realistic case scenarios appear throughout to bring the implementation strategies to life, and the book is packaged with a CD-ROM containing numerous reproducible and customizable forms, surveys, and screening tools, as well as an annotated list of resources for charting and monitoring individual student and classroom progress. RTI in Practice: A Practical Guide to Implementing Effective Evidence-Based Interventions in Your School is a complete resource providing educators and school professionals with the tips?and tools needed for successful RTI program implementation.

Integrates the theory and applications of statistics using R A Course in Statistics with R has been written to bridge the gap between theory and applications and explain how mathematical expressions are converted into R programs. The book has been primarily designed as a useful companion for a Masters student during each semester of the course, but will also help applied statisticians in revisiting the underpinnings of the subject. With this dual goal in mind, the book begins with R basics and quickly covers visualization and exploratory analysis. Probability and statistical inference, inclusive of classical, nonparametric, and Bayesian schools, is developed with definitions, motivations, mathematical expression and R programs in a way which will help the reader to understand the mathematical development as well as R implementation. Linear regression models, experimental designs, multivariate analysis, and categorical data analysis are treated in a way which makes effective use of visualization techniques and the related statistical techniques underlying them through practical applications, and hence helps the reader to achieve a clear understanding of the associated statistical models. Key features: Integrates R basics with statistical concepts Provides graphical presentations inclusive of mathematical expressions Aids understanding of limit theorems of probability with and without the simulation approach Presents detailed algorithmic development of statistical models from scratch Includes practical applications with over 50 data sets

Advanced Statistics with Applications in R fills the gap between several excellent theoretical statistics textbooks and many applied statistics books where teaching reduces to using existing packages. This book looks at what is under the hood. Many statistics issues including the recent crisis with p -value are caused by misunderstanding of statistical concepts due to poor theoretical background of practitioners and applied statisticians. This book is the product of a forty-year experience in teaching of probability and statistics and their applications for solving real-life problems. There are more than 442 examples in the book: basically every probability or statistics concept is illustrated with an example accompanied with an R code. Many examples, such as Who said π? What team is better? The fall of the Roman empire, James Bond chase problem, Black Friday shopping, Free fall equation: Aristotle or Galilei , and many others are intriguing. These examples cover biostatistics, finance, physics and engineering, text and image analysis, epidemiology, spatial statistics, sociology, etc. Advanced Statistics with Applications in R teaches students to use theory for solving real-life problems through computations: there are about 500 R codes and 100 datasets. These data can be freely downloaded from the author's website dartmouth. edu/~eugened. This book is suitable as a text for senior undergraduate students with major in statistics or data science or graduate students. Many researchers who apply statistics on the regular basis find explanation of many fundamental concepts from the theoretical perspective illustrated by concrete real-world applications.