The technique of regression analysis is used so often in business and economics today that an understanding of its use is necessary for almost everyone engaged in the field. This book covers essential elements of building and understanding regression models in a business/economic context in an intuitive manner. The book provides a non-theoretical treatment that is accessible to readers with even a limited statistical background. This book describes exactly how regression models are developed and evaluated. The data used in the book are the kind of data managers are faced with in the real world. The book provides instructions and screen shots for using Microsoft Excel to build business/economic regression models. Upon completion, the reader will be able to interpret the output of the regression models and evaluate the models for accuracy and shortcomings.

Students and instructors of statistics courses using SAS University Edition will welcome this book. Learning fundamental statistics is essential to solving problems with SAS. Essential Statistics Using SAS University Edition demonstrates how to use SAS University Edition to apply a variety of statistical methodologies, from the simple to the not-so-simple, to a range of data sets. Learn how to apply the appropriate statistical method to answer a particular question about a data set, and correctly interpret the numerical results that you obtain. SAS University Edition users who are new to SAS or who need a refresher course will benefit from the statistics overview and topics, such as multiple linear regression, logistic regression, and Poisson regression.

THE DEFINITIVE GUIDE TO NEXTGENERATION DIGITAL MEASUREMENT: INDISPENSABLE INSIGHT FOR BUILDING HIGH-VALUE DIGITAL EXPERIENCES! Helps you capture the knowledge you need to deliver deep personalization at scale Reflects today’s latest insights into digital behavior and consumer psychology For every digital marketer, analyst, and executive who wants to improve performance To win at digital, you must capture the right data, quickly transform it into the right knowledge,and use them both to deliver deep personalization at scale. Conventional digital metrics simply aren’t up to the task. Now, Gary Angel shows how to reinvent digital measurement so it delivers all you need to create richer, more compelling digital experiences. For more than a decade, Angel has helped leading global enterprises succeed at digital. This book reflects all he’s learned. You’ll find valuable guidance on understanding visitor intent… creating customer taxonomies… digital segmentation… integrating VoC research… and using behavioral analysis and controlled experiments to investigate what drives customer choice. Angel will help you measure the value of every digital interaction more accurately, identify specific digital behaviors that predict success, and create a comprehensive measurement paradigm that integrates all your digital spaces. With flawed tools and siloed analytics, you’re blind to what’s really happening online. But you don’t have to be. Gary Angel will help you make the invisible visible… actionable… profitable. Most common digital metrics are virtually useless. They measure the wrong things in the wrong ways. They don’t link digital activity to customer attitudes and behaviors. They don’t work well with today’s powerful analytics tools. Above all, they don’t help you improve your performance. Angel shows how to transform “raw facts” about digital behavior into meaningful knowledge about your visitors… what they were trying to accomplish…how well you helped them… how you can personalize and optimize their digital experiences from now on… how you can use measurement to provide deep personalization at scale. More rigorous, integrated, and usable than any competitive book, Measuring the Digital World will help you create, deliver, and consume digital information with unprecedented sophistication. Whether you’re a digital analyst, marketer, user experience designer, or executive, you’ll find it indispensable. Why conventional digital metrics are arbitrary and misguided Refocus on what you need to know, not what you don’t Capture the “why” Integrate VoC research and behavioral data to build better, richer, more accurate segments Go beyond snapshots: understand your customer’s entire digital experience Understand how your customers’ views and behaviors evolve over time Segment in three dimensions for a multichannel world Treat each channel as part of a larger, integrated, sequential journey

Get the tools you need to use SAS® in clinical trial design!

Unique and multifaceted, Modern Approaches to Clinical Trials Using SAS: Classical, Adaptive, and Bayesian Methods, edited by Sandeep M. Menon and Richard C. Zink, thoroughly covers several domains of modern clinical trial design: classical, group sequential, adaptive, and Bayesian methods that are applicable to and widely used in various phases of pharmaceutical development. Written for biostatisticians, pharmacometricians, clinical developers, and statistical programmers involved in the design, analysis, and interpretation of clinical trials, as well as students in graduate and postgraduate programs in statistics or biostatistics, the book touches on a wide variety of topics, including dose-response and dose-escalation designs; sequential methods to stop trials early for overwhelming efficacy, safety, or futility; Bayesian designs that incorporate historical data; adaptive sample size re-estimation; adaptive randomization to allocate subjects to more effective treatments; and population enrichment designs. Methods are illustrated using clinical trials from diverse therapeutic areas, including dermatology, endocrinology, infectious disease, neurology, oncology, and rheumatology. Individual chapters are authored by renowned contributors, experts, and key opinion leaders from the pharmaceutical/medical device industry or academia. Numerous real-world examples and sample SAS code enable users to readily apply novel clinical trial design and analysis methodologies in practice.

"Mastering RStudio: Develop, Communicate, and Collaborate with R" is your guide to unlocking the potential of RStudio. You'll learn to use RStudio effectively in your data science projects, covering everything from creating R packages to interactive web apps with Shiny. By the end, you'll fully understand how to use RStudio tools to manage projects and share results effectively. What this Book will help me do Gain a comprehensive understanding of the RStudio interface and workflow optimizations. Effectively communicate data insights with R Markdown, including static and interactive documents. Create impactful data visualizations using R's diverse graphical systems and tools. Develop Shiny web applications to showcase and share analytical results. Learn to collaborate on projects using Git and GitHub, and understand R package development workflows. Author(s) Julian Hillebrand and None Nierhoff are experienced R developers with years of practical expertise in data science and software development. They have a passion for teaching how to utilize RStudio effectively. Their approach to writing combines practical examples with thorough explanations, ensuring readers can readily apply concepts to real-world scenarios. Who is it for? This book is ideal for R programmers and analysts seeking to enhance their workflows using RStudio. Whether you're looking to create professional data visualizations, develop R packages, or implement Shiny web applications, this book provides the tools you need. Suitable for those already familiar with basic R programming and fundamental concepts.

This book describes state-of-the-art optimization techniques used to solve problems with adaptive, dynamic, and stochastic features. It presents modern advances in static and dynamic optimization, decision analysis, intelligent systems, evolutionary programming, heuristic optimization, stochastic and adaptive dynamic programming, and adaptive critics. It evaluates optimization methods for handling operational planning, Voltage/VAr, control coordination, vulnerability, reliability, resilience, and reconfiguration issues, providing mathematical formulations, algorithms for implementation, examples, and case studies. It also discusses the limitations of current optimization techniques in meeting the challenges of smart electric grids.

Offering a planned approach for determining cause and effect, DOE Simplified: Practical Tools for Effective Experimentation, Third Edition integrates the authors’ decades of combined experience in providing training, consulting, and computational tools to industrial experimenters. Supplying readers with the statistical means to analyze how numerous variables interact, it is ideal for those seeking breakthroughs in product quality and process efficiency via systematic experimentation. Following in the footsteps of its bestselling predecessors, this edition incorporates a lively approach to learning the fundamentals of the design of experiments (DOE). It lightens up the inherently dry complexities with interesting sidebars and amusing anecdotes. The book explains simple methods for collecting and displaying data and presents comparative experiments for testing hypotheses. Discussing how to block the sources of variation from your analysis, it looks at two-level factorial designs and covers analysis of variance. It also details a four-step planning process for designing and executing experiments that takes statistical power into consideration. This edition includes a major revision of the software that accompanies the book (via download) and sets the stage for introducing experiment designs where the randomization of one or more hard-to-change factors can be restricted. Along these lines, it includes a new chapter on split plots and adds coverage of a number of recent developments in the design and analysis of experiments. Readers have access to case studies, problems, practice experiments, a glossary of terms, and a glossary of statistical symbols, as well as a series of dynamic online lectures that cover the first several chapters of the book.

Creating Data Stories with Tableau Public is a comprehensive guide to building impactful and interactive data visualizations using Tableau Public. Whether you are an investigative journalist, blogger, or data enthusiast, this book takes you through all the essential concepts, from connecting to data sources to publishing your visualizations online. You will learn how to effectively communicate data-driven stories with engaging visuals. What this Book will help me do Understand how to connect and prepare data for Tableau Public visualizations, including tips on cleaning and joining data. Learn about various chart types and their applications to visualize data effectively according to context and message. Discover methods for creating geographic maps and adding meaningful calculations to enhance your visualizations. Master the art of designing dashboards and storytelling with interactive elements like filters and actions. Gain insights on how to publish and embed your Tableau Public visualizations to share your data stories with wider audiences. Author(s) None Ohmann is an accomplished author and educator with rich expertise in data visualization and storytelling. Leveraging a passion for effective communication, None has written extensively on using tools like Tableau Public to bring data to life. As an advocate for accessible and interactive visualizations, None's work bridges technical proficiency and creative expression. Who is it for? This book is perfect for investigative journalists, bloggers, and media professionals eager to incorporate data visualizations into their work. Whether you're a beginner or have some experience with Tableau Public, you'll find practical advice to enhance your abilities. Organizations and teams that deal with data storytelling will also benefit from the clear and actionable strategies outlined in this guide.

This book covers the practical aspects of database design, data cleansing, data analysis, and data protection , among others. The focus is on what you really need to know to create the right database for your small business and to leverage it most effectively to spur growth and revenue. Databases for Small Business is a practical handbook for entrepreneurs, managers, staff, and professionals in small organizations who are not IT specialists but who recognize the need to ramp up their small organizations’ use of data and to round out their own business expertise and office skills with basic database proficiency. Anna Manning—a data scientist who has worked on database design and data analysis in a computer science university research lab, her own small business, and a nonprofit—walks you through the progression of steps that will enable you to extract actionable intelligence and maximum value from your business data in terms of marketing, sales, customer relations, decision making, and business strategy. Dr. Manning illustrates the steps in the book with four running case studies of a small online business, an engineering startup, a small legal firm, and a nonprofit organization.

Learn from state-of-the-art examples in robotics, motors, detection filters, chemical processes, aircraft, and spacecraft. This is a practical reference for industry engineers using MATLAB to solve everyday problems. With MATLAB Recipes: A Problem-Solution Approach you will review contemporary MATLAB coding including the latest language features and use MATLAB as a software development environment including code organization, GUI development, and algorithm design and testing. This book provides practical guidance for using MATLAB to build a body of code you can turn to time and again for solving technical problems in your line of work. Develop algorithms, test them, visualize the results, and pass the code along to others to create a functional code base for your firm.

TO BUILD WINNING TEAMS AND SUCCESSFUL SPORTS BUSINESSES, GUIDE YOUR DECISIONS WITH DATA This up-to-the-minute reference will help you master all three facets of sports analytics – and use it to win! Sports Analytics and Data Science is the most accessible and practical guide to sports analytics for everyone who cares about winning and everyone who is interested in data science. You’ll discover how successful sports analytics blends business and sports savvy, modern information technology, and sophisticated modeling techniques. You’ll master the discipline through realistic sports vignettes and intuitive data visualizations—not complex math. Thomas W. Miller, leader of Northwestern University’s pioneering program in predictive analytics, guides you through defining problems, identifying data, crafting and optimizing models, writing effective R and Python code, interpreting your results, and more. Every chapter focuses on one key sports analytics application. Miller guides you through assessing players and teams, predicting scores and making game-day decisions, crafting brands and marketing messages, increasing revenue and profitability, and much more. Step by step, you’ll learn how analysts transform raw data and analytical models into wins: both on the field and in any sports business. Whether you’re a team executive, coach, fan, fantasy player, or data scientist, this guide will be a powerful source of competitive advantage… in any sport, by any measure. All data sets, extensive R and Python code, and additional examples available for download at http://www.ftpress.com/miller/ This exceptionally complete and practical guide to sports data science and modeling teaches through realistic examples from sports industry economics, marketing, management, performance measurement, and competitive analysis. Thomas W. Miller, faculty director of Northwestern University’s pioneering Predictive Analytics program, shows how to use advanced measures of individual and team performance to judge the competitive position of both individual athletes and teams, and to make more accurate predictions about their future performance. Miller’s modeling techniques draw on methods from economics, accounting, finance, classical and Bayesian statistics, machine learning, simulation, and mathematical programming. Miller illustrates them through realistic case studies, with fully worked examples in both R and Python. Sports Analytics and Data Science will be an invaluable resource for everyone who wants to seriously investigate and more accurately predict player, team, and sports business performance, including students, teachers, sports analysts, sports fans, trainers, coaches, and team and sports business managers. It will also be valuable to all students of analytics and data science who want to build their skills through familiar and accessible sports applications Gain powerful, actionable insights for: Understanding sports markets Assessing players Ranking teams Predicting scores Making game day decisions Crafting marketing messages Promoting brands and products Growing revenues Managing finances Playing what-if games And much more

Contains the complete reference for all Base SAS procedures. Provides information about what each procedure does and, if relevant, the kind of output that it produces.

This guide explains how to apply health economic evaluation techniques to both clinical trial and non-clinical trial data. Through a simple, applied approach using examples and SAS software, the book helps statisticians and researchers in health economics assess cost-effectiveness. It covers trial design, case report form design, quality of life measures, sample sizes, submissions to regulatory authorities for reimbursement, Markov models, cohort models, and decision trees. Examples and case studies are provided at the end of each chapter.

This book shows scientific researchers and applied statisticians from a wide range of fields how to analyze their spatial point pattern data. Making the techniques accessible to non-mathematicians, the authors draw on their 25 years of software development experiences, methodological research, and broad scientific collaborations to deliver a book that clearly and succinctly explains concepts and addresses real scientific questions. The book uses the authors' R package spatstat throughout to process and analyze spatial point pattern data.

Don’t let your fear of finance get in the way of your success. This digital collection, curated by Harvard Business Review, brings together everything a manager needs to know about financial intelligence. It includes Financial Intelligence, called a “must-read” for decision makers without expertise in finance; A Concise Guide to Macroeconomics, which covers the essentials of macroeconomics and examines the core ideas of output, money, and expectations; Essentials of Finance and Budgeting, which explains everything HR professionals need to know to make wise financial decisions; Ahead of the Curve, Joseph H. Ellis’s forecasting method to help managers and investors understand and predict the economic cycles that control their businesses and financial fates; Beyond Budgeting; which offers a coherent management model that overcomes the limitations of traditional budgeting; Preparing a Budget, packed with handy tools, self-tests, and real life examples to help you hone critical skills; and HBR Guide to Finance Basics for Managers, which will give you the tools and confidence you need to master the fundamentals of finance.

Dive into 'Mastering SciPy' to unlock the full potential of the SciPy ecosystem for scientific computation and data analysis. This book thoughtfully combines mathematical concepts with Python programming to tackle real-world computational challenges. What this Book will help me do Effectively implement algorithms for data interpolation, approximation, and function optimization. Develop strategies for managing large datasets and performing linear algebra computations. Create and solve differential equations for scientific modeling and simulations. Apply advanced data analysis, statistical methods, and machine learning algorithms. Utilize computational geometry techniques for applications in engineering and data science. Author(s) The authors, None Blanco-Silva and Francisco Javier B Silva, are practitioners and educators in scientific computing and Python programming. They bring a wealth of experience in using SciPy to solve practical scientific challenges. Their clear and engaging approach makes these complex topics accessible and applicable. Who is it for? This book is tailored for professionals and researchers who use Python and are familiar with numerical methods. If you are looking to deepen your understanding of SciPy's capabilities to solve scientific and engineering problems, this book is ideal for you. Readers with a background in IPython and computational mathematics will benefit the most. Beginners in scientific Python can also learn by following the hands-on examples and clear explanations.

Dive into the world of QlikView with 'QlikView Unlocked,' a comprehensive guide to mastering this powerful business intelligence tool. This book is packed with practical tips, actionable advice, and hands-on techniques to help you design, develop, and optimize QlikView applications efficiently. Whether you're looking to improve your scripting skills, enhance data visualization, or streamline your project workflows, this book covers it all. What this Book will help me do You will learn how to effectively build and configure the QlikView environment for robust and flexible solutions. Gain expertise in applying QlikView development best practices to create optimized and efficient projects. Learn advanced techniques for data modeling and service integration to enhance project scalability. Find out how to troubleshoot and solve common challenges in server deployment and publisher setups. Master data visualization strategies and create stunning, user-friendly dashboards leveraging QlikView's capabilities. Author(s) Roger Stone and Andrew Dove are experienced QlikView developers and consultants with years of practice in delivering optimal business intelligence solutions. They are passionate about sharing their knowledge to empower developers of all levels to realize the potential of QlikView. Their writing is approachable, focusing on practical applications and actionable guidance. Who is it for? This book is ideal for professionals involved in designing or supporting QlikView applications, ranging from beginners getting their first exposure to data-driven decision making to seasoned developers looking for advanced techniques. It's perfect for consultants, data analysts, or anyone seeking to refine their QlikView skills and create impactful business intelligence solutions.

Dive into "Kibana Essentials" and discover how to efficiently analyze data and create visually engaging visualizations and dashboards with Kibana. Whether you are new to Kibana or looking to enhance your skills, this book provides practical guidance to help you apply Kibana features to real-world scenarios. By the end, you'll have the skills to create and apply dashboards that run on Elasticsearch. What this Book will help me do Understand the core features and setup process of Kibana on both Windows and Ubuntu platforms. Master the Discover, Visualize, Dashboard, and Settings functionalities in Kibana. Utilize Elasticsearch's search capabilities to analyze data in Kibana. Create, customize, and share stunning visualizations and dashboards for various use cases. Gain advanced knowledge to tweak Kibana settings for optimized workflows. Author(s) None Gupta is an experienced author and data professional who has worked extensively with Kibana and Elasticsearch technologies. With a passion for simplifying complex concepts, None specializes in breaking down technical topics into digestible, actionable steps. Their practical approach ensures that learners can confidently apply knowledge immediately after reading. Who is it for? This book is for professionals or enthusiasts aiming to delve into data visualization using Kibana. Whether starting from scratch or familiar with similar tools, readers will find the foundational to advanced techniques invaluable. It's especially suited for those who want a practical, hands-on approach to mastering Kibana.

Whether you’re a marketer with development skills or a full-on web developer/analyst, Practical Google Analytics and Google Tag Manager for Developers shows you how to implement Google Analytics using Google Tag Manager to jumpstart your web analytics measurement. There’s a reason that so many organizations use Google Analytics. Effective collection of data with Google Analytics can reduce customer acquisition costs, provide priceless feedback on new product initiatives, and offer insights that will grow a customer or client base. So where does Google Tag Manager fit in? Google Tag Manager allows for unprecedented collaboration between marketing and technical teams, lightning fast updates to your site, and standardization of the most common tags for on-site tracking and marketing efforts. To achieve the rich data you're really after to better serve your users’ needs, you'll need the tools Google Tag Manager provides for a best-in-class implementation of Google Analytics measurement on your site. Written by data evangelist and Google Analytics expert Jonathan Weber and the team at LunaMetrics, this book offers foundational knowledge, a collection of practical Google Tag Manager recipes, well-tested best practices, and troubleshooting tips to get your implementation in tip-top condition. It covers topics including: • Google Analytics implementation via Google Tag Manager • How to customize Google Analytics for your unique situation • Using Google Tag Manager to track and analyze interactions across multiple devices and touch points • How to extract data from Google Analytics and use Google BigQuery to analyze Big Data questions

More than ever, data drives decisions in organizations—and we have more data, and more ways to analyze it, than ever. Yet strategic initiatives continue to fail as often as they did when computers ran on punch cards. Economist and research scientist Alec Levenson says we need a new approach. The problem, Levenson says, is that the business people who devise the strategies and the human resources people who get employees to implement them use completely different analytics. Business analytics can determine if operational priorities aren't being achieved but can't explain why. HR analytics reveal potentially helpful policy and process improvements but can't identify which would have the greatest strategic impact. This book shows how to use an integrated approach to bring these two pieces together. Levenson presents a thorough and realistic treatment of the reasons for and challenges of taking an integrated approach. He provides details on the different parts of both enterprise and human capital analytics that have to be conducted for integration to be successful and includes specific questions to ask, along with examples of applying integrated analytics to address particular organizational challenges. Effective analytics is a team sport. Levenson's approach allows you to get the deepest insights by bringing people together from both the business and HR perspectives to assess what's going on and determine the right solution.