Praise for the Second Edition "This book should be an essential part of the personal library of every practicing statistician."—Technometrics Thoroughly revised and updated, the new edition of Nonparametric Statistical Methods includes additional modern topics and procedures, more practical data sets, and new problems from real-life situations. The book continues to emphasize the importance of nonparametric methods as a significant branch of modern statistics and equips readers with the conceptual and technical skills necessary to select and apply the appropriate procedures for any given situation. Written by leading statisticians, Nonparametric Statistical Methods, Third Edition provides readers with crucial nonparametric techniques in a variety of settings, emphasizing the assumptions underlying the methods. The book provides an extensive array of examples that clearly illustrate how to use nonparametric approaches for handling one- or two-sample location and dispersion problems, dichotomous data, and one-way and two-way layout problems. In addition, the Third Edition features: The use of the freely available R software to aid in computation and simulation, including many new R programs written explicitly for this new edition New chapters that address density estimation, wavelets, smoothing, ranked set sampling, and Bayesian nonparametrics Problems that illustrate examples from agricultural science, astronomy, biology, criminology, education, engineering, environmental science, geology, home economics, medicine, oceanography, physics, psychology, sociology, and space science Nonparametric Statistical Methods, Third Edition is an excellent reference for applied statisticians and practitioners who seek a review of nonparametric methods and their relevant applications. The book is also an ideal textbook for upper-undergraduate and first-year graduate courses in applied nonparametric statistics.

This work enables readers to obtain the mathematical and statistical background required in the current financial and actuarial industries. It also advances the application and theory of statistics in modern financial and actuarial modeling. This second edition adds a substantial amount of new material, including Excel exercises with solutions; nomenclature and notations standard to the actuarial field; a new chapter on Markov chains and actuarial applications; expanded discussions on simulation, surplus models, and ruin computations; and much more.

This best-selling engineering statistics text provides a practical approach that is more oriented to engineering and the chemical and physical sciences than many similar texts. It is packed with unique problem sets that reflect realistic situations engineers will encounter in their working lives. This text shows how statistics, the science of data is just as important for engineers as the mechanical, electrical, and materials sciences.

THE COMPLETE COLLECTION NECESSARY FOR A CONCRETE UNDERSTANDING OF PROBABILITY Written in a clear, accessible, and comprehensive manner, the Handbook of Probability presents the fundamentals of probability with an emphasis on the balance of theory, application, and methodology. Utilizing basic examples throughout, the handbook expertly transitions between concepts and practice to allow readers an inclusive introduction to the field of probability. The book provides a useful format with self-contained chapters, allowing the reader easy and quick reference. Each chapter includes an introduction, historical background, theory and applications, algorithms, and exercises. The Handbook of Probability offers coverage of: Probability Space Probability Measure Random Variables Random Vectors in Rn Characteristic Function Moment Generating Function Gaussian Random Vectors Convergence Types Limit Theorems The Handbook of Probability is an ideal resource for researchers and practitioners in numerous fields, such as mathematics, statistics, operations research, engineering, medicine, and finance, as well as a useful text for graduate students.

This text is an unbound, binder-ready edition. Business Statistics: For Contemporary Decision Making, 8th Edition continues the tradition of presenting and explaining the wonders of business statistics through the use of clear, complete, student-friendly pedagogy. Ken Black's text equips readers with the quantitative decision-making skills and analysis techniques you need to make smart decisions based on real-world data.

"IBM SPSS Modeler Cookbook" is your practical guide to mastering data mining with IBM SPSS Modeler. This comprehensive book takes you beyond the basics, offering expert insights, time-saving techniques, and powerful workflows to grow your skills and elevate your analytical abilities. You will learn to apply the CRISP-DM methodology, efficiently prepare and explore data, build advanced models, and confidently incorporate analytical results into your business decisions. What this Book will help me do Effectively apply the CRISP-DM standard process to organize your data mining projects. Leverage efficient techniques for data extraction, transformation, and preparation. Develop and evaluate predictive models for practical applications in your organization. Enhance your models by utilizing advanced features and expert tips. Automate and streamline your data mining process with scripting for ultimate control. Author(s) Keith McCormick and None Abbott are seasoned data mining professionals with deep expertise in IBM SPSS Modeler and predictive analytics. Together, they have extensive experience in consulting, training, and applying advanced analytical techniques across industries. Through their approachable and insightful writing style, they share practical knowledge and expert workflows to empower readers. Who is it for? This book is designed for individuals who have basic experience with IBM SPSS Modeler and aspire to deepen their expertise. Whether you are a data analyst looking to advance your analytical capabilities or a professional aiming to integrate data-driven solutions into your organization, this book provides the knowledge and practical guidance you need to take the next step in your data mining journey.

A major tool for quality control and management, statistical process control (SPC) monitors sequential processes, such as production lines and Internet traffic, to ensure that they work stably and satisfactorily. Along with covering traditional methods, Introduction to Statistical Process Control describes many recent SPC methods that improve upon the more established techniques. The author—a leading researcher on SPC—shows how these methods can handle new applications. After exploring the role of SPC and other statistical methods in quality control and management, the book covers basic statistical concepts and methods useful in SPC. It then systematically describes traditional SPC charts, including the Shewhart, CUSUM, and EWMA charts, as well as recent control charts based on change-point detection and fundamental multivariate SPC charts under the normality assumption. The text also introduces novel univariate and multivariate control charts for cases when the normality assumption is invalid and discusses control charts for profile monitoring. All computations in the examples are solved using R, with R functions and datasets available for download on the author’s website. Offering a systematic description of both traditional and newer SPC methods, this book is ideal as a primary textbook for a one-semester course in disciplines concerned with process quality control, such as statistics, industrial and systems engineering, and management sciences. It can also be used as a supplemental textbook for courses on quality improvement and system management. In addition, the book provides researchers with many useful, recent research results on SPC and gives quality control practitioners helpful guidelines on implementing up-to-date SPC techniques.

When ricocheting a solution that involves analytics, the mainframe might not be the first platform that comes to mind. However, the IBM® System z® group has developed some innovative solutions that include the well-respected mainframe benefits. This book describes a workshop that demonstrates the use of real-time advanced analytics for enhancing core banking decisions using a loan origination example. The workshop is a live hands-on experience of the entire process from analytics modeling to deployment of real-time scoring services for use on IBM z/OS®. In this IBM Redbooks® publication, we include a facilitator guide chapter as well as a participant guide chapter. The facilitator guide includes information about the preparation, such as the needed material, resources, and steps to set up and run this workshop. The participant guide shows step-by-step the tasks for a successful learning experience. The goal of the first hands-on exercise is to learn how to use IBM SPSS® Modeler for Analytics modeling. This provides the basis for the next exercise "Configuring risk assessment in SPSS Decision Management". In the third exercise, the participant experiences how real-time scoring can be implemented on a System z. This publication is written for consultants, IT architects, and IT administrators who want to become familiar with SPSS and analytics solutions on the System z.

If you know how to program with Python, and know a little about probability, you’re ready to tackle Bayesian statistics. This book shows you how to use Python code instead of math to help you learn Bayesian fundamentals. Once you get the math out of the way, you’ll be able to apply these techniques to real-world problems.

The highly prized ability to make financial plans with some certainty about the future comes from the core fields of economics. In recent years the availability of more data, analytical tools of greater precision, and ex post studies of business decisions have increased demand for information about economic forecasting. Volumes 2A and 2B, which follows Nobel laureate Clive Granger's Volume 1 (2006), concentrate on two major subjects. Volume 2A covers innovations in methodologies, specifically macroforecasting and forecasting financial variables. Volume 2B investigates commercial applications, with sections on forecasters' objectives and methodologies. Experts provide surveys of a large range of literature scattered across applied and theoretical statistics journals as well as econometrics and empirical economics journals. The Handbook of Economic Forecasting Volumes 2A and 2B provide a unique compilation of chapters giving a coherent overview of forecasting theory and applications in one place and with up-to-date accounts of all major conceptual issues. Focuses on innovation in economic forecasting via industry applications Presents coherent summaries of subjects in economic forecasting that stretch from methodologies to applications Makes details about economic forecasting accessible to scholars in fields outside economics

The highly prized ability to make financial plans with some certainty about the future comes from the core fields of economics. In recent years the availability of more data, analytical tools of greater precision, and ex post studies of business decisions have increased demand for information about economic forecasting. Volumes 2A and 2B, which follows Nobel laureate Clive Granger's Volume 1 (2006), concentrate on two major subjects. Volume 2A covers innovations in methodologies, specifically macroforecasting and forecasting financial variables. Volume 2B investigates commercial applications, with sections on forecasters' objectives and methodologies. Experts provide surveys of a large range of literature scattered across applied and theoretical statistics journals as well as econometrics and empirical economics journals. The Handbook of Economic Forecasting Volumes 2A and 2B provide a unique compilation of chapters giving a coherent overview of forecasting theory and applications in one place and with up-to-date accounts of all major conceptual issues. Focuses on innovation in economic forecasting via industry applications Presents coherent summaries of subjects in economic forecasting that stretch from methodologies to applications Makes details about economic forecasting accessible to scholars in fields outside economics

Credible Checklists and Quality Questionnaires starts off with an examination of the critical but commonly overlooked checklist method. In the second chapter, questionnaires and surveys are discussed. Asking questions sounds simple, but the hard truth is that asking questions (and designing questionnaires) is a difficult task. This chapter discusses being mindful of the choice of words, order of questions and how early questions influence later questions, answer scales and how they impact the user response, questionnaire design, and much more. The final chapter provides examples of some common questionnaires (both free and fee-based) for assessing the usability of products. After reading this book, readers will be able to use these user design tools with greater confidence and certainty.

An updated new edition of the comprehensive guide to better business forecasting Many companies still look at quantitative forecasting methods with suspicion, but a new awareness is emerging across many industries as more businesses and professionals recognize the value of integrating demand data (point-of-sale and syndicated scanner data) into the forecasting process. Demand-Driven Forecasting equips you with solutions that can sense, shape, and predict future demand using highly sophisticated methods and tools. From a review of the most basic forecasting methods to the most advanced and innovative techniques in use today, this guide explains demand-driven forecasting, offering a fundamental understanding of the quantitative methods used to sense, shape, and predict future demand within a structured process. Offering a complete overview of the latest business forecasting concepts and applications, this revised Second Edition of Demand-Driven Forecasting is the perfect guide for professionals who need to improve the accuracy of their sales forecasts. Completely updated to include the very latest concepts and methods in forecasting Includes real case studies and examples, actual data, and graphical displays and tables to illustrate how effective implementation works Ideal for CEOs, CFOs, CMOs, vice presidents of supply chain, vice presidents of demand forecasting and planning, directors of demand forecasting and planning, supply chain managers, demand planning managers, marketing analysts, forecasting analysts, financial managers, and any other professional who produces or contributes to forecasts Accurate forecasting is vital to success in today's challenging business climate. Demand-Driven Forecasting offers proven and effective insight on making sure your forecasts are right on the money.

Designing and Conducting Business Surveys provides a coherent overview of the business survey process, from start to finish. It uniquely integrates an understanding of how businesses operate, a total survey error approach to data quality that focuses specifically on business surveys, and sound project management principles. The book brings together what is currently known about planning, designing, and conducting business surveys, with producing and disseminating statistics or other research results from the collected data. This knowledge draws upon a variety of disciplines such as survey methodology, organizational sciences, sociology, psychology, and statistical methods. The contents of the book formulate a comprehensive guide to scholarly material previously dispersed among books, journal articles, and conference papers. This book provides guidelines that will help the reader make educated trade-off decisions that minimize survey errors, costs, and response burden, while being attentive to survey data quality. Major topics include: Determining the survey content, considering user needs, the business context, and total survey quality Planning the survey as a project Sampling frames, procedures, and methods Questionnaire design and testing for self-administered paper, web, and mixed-mode surveys Survey communication design to obtain responses and facilitate the business response process Conducting and managing the survey using paradata and project management tools Data processing, including capture, editing, and imputation, and dissemination of statistical outputs Designing and Conducting Business Surveys is an indispensable resource for anyone involved in designing and/or conducting business or organizational surveys at statistical institutes, central banks, survey organizations, etc.; producing statistics or other research results from business surveys at universities, research organizations, etc.; or using data produced from business surveys. The book also lays a foundation for new areas of research in business surveys.

Student-Friendly Coverage of Probability, Statistical Methods, Simulation, and Modeling ToolsIncorporating feedback from instructors and researchers who used the previous edition, Probability and Statistics for Computer Scientists, Second Edition helps students understand general methods of stochastic modeling, simulation, and data analysis; make o

Score your highest in biostatistics Biostatistics is a required course for students of medicine, epidemiology, forestry, agriculture, bioinformatics, and public health. In years past this course has been mainly a graduate-level requirement; however its application is growing and course offerings at the undergraduate level are exploding. Biostatistics For Dummies is an excellent resource for those taking a course, as well as for those in need of a handy reference to this complex material. Biostatisticians—analysts of biological data—are charged with finding answers to some of the world's most pressing health questions: how safe or effective are drugs hitting the market today? What causes autism? What are the risk factors for cardiovascular disease? Are those risk factors different for men and women or different ethnic groups? Biostatistics For Dummies examines these and other questions associated with the study of biostatistics. Provides plain-English explanations of techniques and clinical examples to help Serves as an excellent course supplement for those struggling with the complexities of the biostatistics Tracks to a typical, introductory biostatistics course Biostatistics For Dummies is an excellent resource for anyone looking to succeed in this difficult course.

An up-to-date look at point and figure charting from one of the foremost authorities in the field If you're looking for an investment approach that has stood the test of time—during both bull and bear markets—and is easy enough to learn, whether you're an expert or aspiring investor, then Point and Figure Charting, Fourth Edition is the book for you. Filled with in-depth insights and expert advice, this practical guide will help you grow your assets in any market. In this reliable resource, the world's top point and figure charting expert, Tom Dorsey returns to explain how traders and investors alike can use this classic technique—borne out of the irrefutable laws of supply and demand—to identify and capitalize on market trends. Describes, step-by-step, how to create, maintain, and interpret your own point and figure charts with regard to markets, sectors, and individual securities Explains how to use other indicators, including moving averages, advance-decline lines, and relative strength to augment point and figure analysis Reveals how to use this approach to track and forecast market prices and develop an overall investment strategy Skillfully explains how to use point and figure analysis to evaluate the strength of international markets and rotate exposure from country to country Today's investment arena is filled with a variety of strategies that never seem to deliver on what they promise. But there is one approach to investment analysis that has proven itself in all types of markets, and it's found right here in Point and Figure Charting, Fourth Edition.

How to make simple sense of complex statistics--from the author of Numbers Rule Your World We live in a world of Big Data--and it's getting bigger every day. Virtually every choice we make hinges on how someone generates data . . . and how someone else interprets it--whether we realize it or not. Where do you send your child for the best education? Big Data. Which airline should you choose to ensure a timely arrival? Big Data. Who will you vote for in the next election? Big Data. The problem is, the more data we have, the more difficult it is to interpret it. From world leaders to average citizens, everyone is prone to making critical decisions based on poor data interpretations. In Numbersense, expert statistician Kaiser Fung explains when you should accept the conclusions of the Big Data "experts"--and when you should say, "Wait . . . what?" He delves deeply into a wide range of topics, offering the answers to important questions, such as: How does the college ranking system really work? Can an obesity measure solve America's biggest healthcare crisis? Should you trust current unemployment data issued by the government? How do you improve your fantasy sports team? Should you worry about businesses that track your data? Don't take for granted statements made in the media, by our leaders, or even by your best friend. We're on information overload today, and there's a lot of bad information out there. Numbersense gives you the insight into how Big Data interpretation works--and how it too often doesn't work. You won't come away with the skills of a professional statistician. But you will have a keen understanding of the data traps even the best statisticians can fall into, and you'll trust the mental alarm that goes off in your head when something just doesn't seem to add up. Praise for Numbersense " Numbersense correctly puts the emphasis not on the size of big data, but on the analysis of it. Lots of fun stories, plenty of lessons learned—in short, a great way to acquire your own sense of numbers!" Thomas H. Davenport, coauthor of Competing on Analytics and President’s Distinguished Professor of IT and Management, Babson College "Kaiser’s accessible business book will blow your mind like no other. You’ll be smarter, and you won’t even realize it. Buy. It. Now." Avinash Kaushik, Digital Marketing Evangelist, Google, and author, Web Analytics 2.0 "Each story in Numbersense goes deep into what you have to think about before you trust the numbers. Kaiser Fung ably demonstrates that it takes skill and resourcefulness to make the numbers confess their meaning." John Sall, Executive Vice President, SAS Institute "Kaiser Fung breaks the bad news—a ton more data is no panacea—but then has got your back, revealing the pitfalls of analysis with stimulating stories from the front lines of business, politics, health care, government, and education. The remedy isn’t an advanced degree, nor is it common sense. You need Numbersense." Eric Siegel, founder, Predictive Analytics World, and author, Predictive Analytics "I laughed my way through this superb-useful-fun book and learned and relearned a lot. Highly recommended!" Tom Peters, author of In Search of Excellence

Solar Energy Forecasting and Resource Assessment is a vital text for solar energy professionals, addressing a critical gap in the core literature of the field. As major barriers to solar energy implementation, such as materials cost and low conversion efficiency, continue to fall, issues of intermittency and reliability have come to the fore. Scrutiny from solar project developers and their financiers on the accuracy of long-term resource projections and grid operators’ concerns about variable short-term power generation have made the field of solar forecasting and resource assessment pivotally important. This volume provides an authoritative voice on the topic, incorporating contributions from an internationally recognized group of top authors from both industry and academia, focused on providing information from underlying scientific fundamentals to practical applications and emphasizing the latest technological developments driving this discipline forward. The only reference dedicated to forecasting and assessing solar resources enables a complete understanding of the state of the art from the world’s most renowned experts. Demonstrates how to derive reliable data on solar resource availability and variability at specific locations to support accurate prediction of solar plant performance and attendant financial analysis. Provides cutting-edge information on recent advances in solar forecasting through monitoring, satellite and ground remote sensing, and numerical weather prediction.

This book helps readers obtain an in-depth understanding of statistical theory by working on and reviewing solutions to interesting and challenging exercises of practical importance. Unlike similar books, this one incorporates many exercises that apply to real-world settings and provides much more thorough solutions. The exercises and selected detailed solutions cover from basic probability theory through to the theory of statistical inference. By mastering the theoretical statistical strategies necessary to solve the exercises, readers will be prepared to successfully study even higher-level statistical theory.