Your guide to quickly turn data into results. Transform your skills, data, and business—and create your own BI solutions using software you already know and love: Microsoft Excel. Two business intelligence (BI) experts take you inside PowerPivot functionality for Excel® 2013, with a focus on real world scenarios, problem-solving, and data modeling. You'll learn how to quickly turn mass quantities of data into meaningful information and on-the-job results—no programming required! Understand the differences between PowerPivot for Self Service BI and SQL Server Analysis Services for Corporate BI Extend your existing data-analysis skills to create your own BI solutions Quickly manipulate large data sets, often in millions of rows Perform simple-to-sophisticated calculations and what-if analysis Create complex reporting systems with data modeling and Data Analysis Expressions Share your results effortlessly across your organization using Microsoft SharePoint®

Suitable for statisticians, mathematicians, actuaries, and students interested in the problems of insurance and analysis of lifetimes, this book presents contemporary statistical techniques for analyzing life distributions and life insurance problems. It mainly focuses on the analysis of an individual life and describes statistical methods based on empirical and related processes. The text not only contains traditional material but also incorporates new problems and techniques not discussed in existing actuarial literature. Coverage ranges from analyzing the tails of distributions of lifetimes to modeling population dynamics with migrations.

This easy-to-understand guide makes SEM accessible to all users. This second edition contains new material on sample-size estimation for path analysis and structural equation modeling. In a single user-friendly volume, students and researchers will find all the information they need in order to master SAS basics before moving on to factor analysis, path analysis, and other advanced statistical procedures.

SAS Server Pages have been used by SAS developers as a way of creating custom user interfaces for Web-based applications. This enhanced book offers information on how to create SAS Server Pages using the SAS 9.3 experimental procedure PROC STREAM, providing users with a foundation technology that greatly expands the capabilities of SAS for dynamic and rich content generation. By combining PROC STREAM and the Macro facility, SAS can now more easily generate any type of markup or text-based content such as HTML, XML, and CSV.

Exclusively available in electronic format, this book provides more extensive and flexible ways to develop applications using video examples of a wide range of PROC STREAM and SAS Server Pages techniques, including both Web applications and Base SAS implementations. Users can see results immediately and can access additional content and information online through embedded links. It also offers basic how-to documentation on PROC STREAM and an overview of a Portal Reporting Framework that illustrates creating custom user interfaces for stored processes within the SAS Portal.

Ideal for SAS programmers who have some knowledge of the Macro facility as well as BI users, SAS Server Pages: Generating Dynamic Content removes the difficulties associated with HTML-based content creation while providing a resource on using PROC STREAM in a dynamic, enhanced format.

Whether you’re a startup founder trying to disrupt an industry or an entrepreneur trying to provoke change from within, your biggest challenge is creating a product people actually want. Lean Analytics steers you in the right direction. This book shows you how to validate your initial idea, find the right customers, decide what to build, how to monetize your business, and how to spread the word. Packed with more than thirty case studies and insights from over a hundred business experts, Lean Analytics provides you with hard-won, real-world information no entrepreneur can afford to go without. Understand Lean Startup, analytics fundamentals, and the data-driven mindset Look at six sample business models and how they map to new ventures of all sizes Find the One Metric That Matters to you Learn how to draw a line in the sand, so you’ll know it’s time to move forward Apply Lean Analytics principles to large enterprises and established products

As the Solutions Manual, this book is meant to accompany the main title, Introduction to Linear Regression Analysis, Fifth Edition. Clearly balancing theory with applications, this book describes both the conventional and less common uses of linear regression in the practical context of today's mathematical and scientific research. Beginning with a general introduction to regression modeling, including typical applications, the book then outlines a host of technical tools that form the linear regression analytical arsenal, including: basic inference procedures and introductory aspects of model adequacy checking; how transformations and weighted least squares can be used to resolve problems of model inadequacy; how to deal with influential observations; and polynomial regression models and their variations. The book also includes material on regression models with autocorrelated errors, bootstrapping regression estimates, classification and regression trees, and regression model validation.

Since many practical engineering problems must be solved numerically, this text provides instruction on using numerical methods and Excel/VBA for chemical and biomolecular engineering problems, covering a broad range of application areas. It also includes an introduction to MATLAB that is made easier to learn after studying the programming tools in previous chapters. Each chapter contains examples that show in detail how a particular numerical method or programming methodology can be implemented. The chapters also contain end-of-chapter exercises, with solutions provided.

A road map for implementing quantitative financial models Financial Derivative and Energy Market Valuation brings the application of financial models to a higher level by helping readers capture the true behavior of energy markets and related financial derivatives. The book provides readers with a range of statistical and quantitative techniques and demonstrates how to implement the presented concepts and methods in Matlab. Featuring an unparalleled level of detail, this unique work provides the underlying theory and various advanced topics without requiring a prior high-level understanding of mathematics or finance. In addition to a self-contained treatment of applied topics such as modern Fourier-based analysis and affine transforms, Financial Derivative and Energy Market Valuation also: Provides the derivation, numerical implementation, and documentation of the corresponding Matlab for each topic Extends seminal works developed over the last four decades to derive and utilize present-day financial models Shows how to use applied methods such as fast Fourier transforms to generate statistical distributions for option pricing Includes all Matlab code for readers wishing to replicate the figures found throughout the book Thorough, practical, and easy to use, Financial Derivative and Energy Market Valuation is a first-rate guide for readers who want to learn how to use advanced numerical methods to implement and apply state-of-the-art financial models. The book is also ideal for graduate-level courses in quantitative finance, mathematical finance, and financial engineering.

Probability, Statistics and Random Processes is designed to meet the requirements of students and is intended for beginners to help them understand the concepts from the first principles. Spread across 16 chapters, it discusses the theoretical aspects that have been refined and updated to reflect the current developments in the subjects. It expounds on theoretical concepts that have immense practical applications, giving adequate proofs to establish significant theorems.

Managing Data in Motion describes techniques that have been developed for significantly reducing the complexity of managing system interfaces and enabling scalable architectures. Author April Reeve brings over two decades of experience to present a vendor-neutral approach to moving data between computing environments and systems. Readers will learn the techniques, technologies, and best practices for managing the passage of data between computer systems and integrating disparate data together in an enterprise environment. The average enterprise's computing environment is comprised of hundreds to thousands computer systems that have been built, purchased, and acquired over time. The data from these various systems needs to be integrated for reporting and analysis, shared for business transaction processing, and converted from one format to another when old systems are replaced and new systems are acquired. The management of the "data in motion" in organizations is rapidly becoming one of the biggest concerns for business and IT management. Data warehousing and conversion, real-time data integration, and cloud and "big data" applications are just a few of the challenges facing organizations and businesses today. Managing Data in Motion tackles these and other topics in a style easily understood by business and IT managers as well as programmers and architects. Presents a vendor-neutral overview of the different technologies and techniques for moving data between computer systems including the emerging solutions for unstructured as well as structured data types Explains, in non-technical terms, the architecture and components required to perform data integration Describes how to reduce the complexity of managing system interfaces and enable a scalable data architecture that can handle the dimensions of "Big Data"

Underwater Acoustic Modeling and Simulation, Fourth Edition continues to provide the most authoritative overview of currently available propagation, noise, reverberation, and sonar-performance models. This fourth edition of a bestseller discusses the fundamental processes involved in simulating the performance of underwater acoustic systems and emphasizes the importance of applying the proper modeling resources to simulate the behavior of sound in virtual ocean environments. New to the Fourth Edition Extensive new material that addresses recent advances in inverse techniques and marine-mammal protection Problem sets in each chapter Updated and expanded inventories of available models Designed for readers with an understanding of underwater acoustics but who are unfamiliar with the various aspects of modeling, the book includes sufficient mathematical derivations to demonstrate model formulations and provides guidelines for selecting and using the models. Examples of each type of model illustrate model formulations, model assumptions, and algorithm efficiency. Simulation case studies are also included to demonstrate practical applications. Providing a thorough source of information on modeling resources, this book examines the translation of our physical understanding of sound in the sea into mathematical models that simulate acoustic propagation, noise, and reverberation in the ocean. The text shows how these models are used to predict and diagnose the performance of complex sonar systems operating in the undersea environment.

Part of the Jones and Bartlett Learning International Series in Mathematics

Written for the one-term introductory probability and statistics course for mid- to upper-level math and science majors, Essentials of Mathematical Statistics combines the topics generally found in main-stream elementary statistics books with the essentials of the underlying theory. The book begins with an axiomatic treatment of probability followed by chapters on discrete and continuous random variables and their associated distributions. It then introduces basic statistical concepts including summarizing data and interval parameter estimation, stressing the connection between probability and statistics. Final chapters introduce hypothesis testing, regression, and non-parametric techniques. All chapters provide a balance between conceptual understanding and theoretical understanding of the topics at hand.

Key Features of Essentials of Mathematical Statistics:

• End-of-section exercises range from computational to conceptual to theoretical.
• Many sections include a sub-section titled “Software Calculations” which gives detailed descriptions of how to perform the calculations discussed in the section using the software Minitab, R, Excel, and the TI-83/84 calculators.
• Provides a clear balance between conceptual understanding and theoretical understanding
• Exercises throughout vary in level of difficulty and scope.

"The Freakonomics of big data." —Stein Kretsinger, founding executive of Advertising.com; former lead analyst at Capital One This book is easily understood by all readers. Rather than a "how to" for hands-on techies, the book entices lay-readers and experts alike by covering new case studies and the latest state-of-the-art techniques. You have been predicted — by companies, governments, law enforcement, hospitals, and universities. Their computers say, "I knew you were going to do that!" These institutions are seizing upon the power to predict whether you're going to click, buy, lie, or die. Why? For good reason: predicting human behavior combats financial risk, fortifies healthcare, conquers spam, toughens crime fighting, and boosts sales. How? Prediction is powered by the world's most potent, booming unnatural resource: data. Accumulated in large part as the by-product of routine tasks, data is the unsalted, flavorless residue deposited en masse as organizations churn away. Surprise! This heap of refuse is a gold mine. Big data embodies an extraordinary wealth of experience from which to learn. Predictive analytics unleashes the power of data. With this technology, the computer literally learns from data how to predict the future behavior of individuals. Perfect prediction is not possible, but putting odds on the future — lifting a bit of the fog off our hazy view of tomorrow — means pay dirt. In this rich, entertaining primer, former Columbia University professor and Predictive Analytics World founder Eric Siegel reveals the power and perils of prediction: What type of mortgage risk Chase Bank predicted before the recession. Predicting which people will drop out of school, cancel a subscription, or get divorced before they are even aware of it themselves. Why early retirement decreases life expectancy and vegetarians miss fewer flights. Five reasons why organizations predict death, including one health insurance company. How U.S. Bank, European wireless carrier Telenor, and Obama's 2012 campaign calculated the way to most strongly influence each individual. How IBM's Watson computer used predictive modeling to answer questions and beat the human champs on TV's Jeopardy! How companies ascertain untold, private truths — how Target figures out you're pregnant and Hewlett-Packard deduces you're about to quit your job. How judges and parole boards rely on crime-predicting computers to decide who stays in prison and who goes free. What's predicted by the BBC, Citibank, ConEd, Facebook, Ford, Google, IBM, the IRS, Match.com, MTV, Netflix, Pandora, PayPal, Pfizer, and Wikipedia. A truly omnipresent science, predictive analytics affects everyone, every day. Although largely unseen, it drives millions of decisions, determining whom to call, mail, investigate, incarcerate, set up on a date, or medicate. Predictive analytics transcends human perception. This book's final chapter answers the riddle: What often happens to you that cannot be witnessed, and that you can't even be sure has happened afterward — but that can be predicted in advance? Whether you are a consumer of it — or consumed by it — get a handle on the power of Predictive Analytics.

A highly accessible alternative approach to basic statistics Praise for the First Edition: "Certainly one of the most impressive little paperback 200-page introductory statistics books that I will ever see . . . it would make a good nightstand book for every statistician."—Technometrics Written in a highly accessible style, Introduction to Statistics through Resampling Methods and R, Second Edition guides students in the understanding of descriptive statistics, estimation, hypothesis testing, and model building. The book emphasizes the discovery method, enabling readers to ascertain solutions on their own rather than simply copy answers or apply a formula by rote. The Second Edition utilizes the R programming language to simplify tedious computations, illustrate new concepts, and assist readers in completing exercises. The text facilitates quick learning through the use of: More than 250 exercises—with selected "hints"—scattered throughout to stimulate readers' thinking and to actively engage them in applying their newfound skills An increased focus on why a method is introduced Multiple explanations of basic concepts Real-life applications in a variety of disciplines Dozens of thought-provoking, problem-solving questions in the final chapter to assist readers in applying statistics to real-life applications Introduction to Statistics through Resampling Methods and R, Second Edition is an excellent resource for students and practitioners in the fields of agriculture, astrophysics, bacteriology, biology, botany, business, climatology, clinical trials, economics, education, epidemiology, genetics, geology, growth processes, hospital administration, law, manufacturing, marketing, medicine, mycology, physics, political science, psychology, social welfare, sports, and toxicology who want to master and learn to apply statistical methods.

is organized around applications, first introducing the actual behavior of specific signals and then using them to motivate the presentation of mathematical concepts. Tervo sequences the presentation of the major transforms by their complexity: first Fourier, then Laplace, and finally the z-transform. Practical Signals Theory with MATLAB Applications The goal is to help students who can't visualize phenomena from an equation to develop their intuition and learn to analyze signals by inspection. Finally, most examples and problems are designed to use MATLAB, making the presentation more in line with modern engineering practice.

Art Carpenter demystifies the powerful REPORT procedure and shows you how to incorporate this highly flexible and customizable procedure into your SAS reporting programs. Combining his years of SAS experience with a talent for instruction, Art offers clear and comprehensive coverage that demonstrates how valuable this procedure is for both summarizing and displaying data. Illustrated with more than two hundred examples and sample exercises to reinforce your learning, Carpenter's Complete Guide to the SAS REPORT Procedure provides you with information that you can put to immediate use. The text is divided into three distinct sections. Part 1 introduces you to PROC REPORT, showing you how it works and "thinks." This section is designed to be read linearly by users who are unfamiliar with the procedure. Part 2 is a collection of increasingly more complex examples that feature advanced options and capabilities. It also introduces the relationship between PROC REPORT and the Output Delivery System (ODS). Part 3 incorporates the options and statements described in Parts 1 and 2 into a series of examples that highlight many of the extended capabilities of PROC REPORT. Included in this section is a discussion of a few ODS statements and options that might be useful to a PROC REPORT programmer, plus an in-depth look at the PROC REPORT process itself, especially as it relates to the execution of compute blocks. Art's author page at support.sas.com/carpenter includes the following bonus material: example SAS data sets, example results, and a compilation of nearly 100 related conference papers. This book is part of the SAS Press program.

Chi-Squared Goodness of Fit Tests with Applications provides a thorough and complete context for the theoretical basis and implementation of Pearson’s monumental contribution and its wide applicability for chi-squared goodness of fit tests. The book is ideal for researchers and scientists conducting statistical analysis in processing of experimental data as well as to students and practitioners with a good mathematical background who use statistical methods. The historical context, especially Chapter 7, provides great insight into importance of this subject with an authoritative author team. This reference includes the most recent application developments in using these methods and models. Systematic presentation with interesting historical context and coverage of the fundamentals of the subject Presents modern model validity methods, graphical techniques, and computer-intensive methods Recent research and a variety of open problems Interesting real-life examples for practitioners

Provides an introduction to basic structures of probability with a view towards applications in information technology A First Course in Probability and Markov Chains presents an introduction to the basic elements in probability and focuses on two main areas. The first part explores notions and structures in probability, including combinatorics, probability measures, probability distributions, conditional probability, inclusion-exclusion formulas, random variables, dispersion indexes, independent random variables as well as weak and strong laws of large numbers and central limit theorem. In the second part of the book, focus is given to Discrete Time Discrete Markov Chains which is addressed together with an introduction to Poisson processes and Continuous Time Discrete Markov Chains. This book also looks at making use of measure theory notations that unify all the presentation, in particular avoiding the separate treatment of continuous and discrete distributions. A First Course in Probability and Markov Chains: Presents the basic elements of probability. Explores elementary probability with combinatorics, uniform probability, the inclusion-exclusion principle, independence and convergence of random variables. Features applications of Law of Large Numbers. Introduces Bernoulli and Poisson processes as well as discrete and continuous time Markov Chains with discrete states. Includes illustrations and examples throughout, along with solutions to problems featured in this book. The authors present a unified and comprehensive overview of probability and Markov Chains aimed at educating engineers working with probability and statistics as well as advanced undergraduate students in sciences and engineering with a basic background in mathematical analysis and linear algebra.

Supply chain professionals: master pioneering techniques for integrating demand and supply, and create demand forecasts that are far more accurate and useful! In Demand and Supply Integration, Dr. Mark Moon presents the specific design characteristics of a world-class demand forecasting management process, showing how to effectively integrate demand forecasting within a comprehensive Demand and Supply Integration (DSI) process. Writing for supply chain professionals in any business, government agency, or military procurement organization, Moon explains what DSI is, how it differs from approaches such as SandOP, and how to recognize the symptoms of failures to sufficiently integrate demand and supply. He outlines the key characteristics of successful DSI implementations, shows how to approach Demand Forecasting as a management process, and guides you through understanding, selecting, and applying the best available qualitative and quantitative forecasting techniques. You'll learn how to thoroughly reflect market intelligence in your forecasts; measure your forecasting performance; implement state-of-the-art demand forecasting systems; manage Demand Reviews, and much more. For wide audiences of supply chain, logistics, and operations management professionals at all levels, from analyst and manager to Director, Vice President, and Chief Supply Chain Officer; and for researchers and graduate students in the field.

CRUNCH ANY DATA, FROM ANY SOURCE, QUICKLY AND EASILY, WITH EXCEL 2013 PIVOT TABLES! Use Excel 2013 pivot tables and pivot charts to produce powerful, dynamic reports in minutes instead of hours… understand exactly what’s going on in your business… take control, and stay in control! Even if you’ve never created a pivot table before, this book will help you leverage all their amazing flexibility and analytical power. In just the first seven chapters, you learn how to generate complex pivot reports complete with drill-down capabilities and accompanying charts. Then, you go even further, discovering how to build a comprehensive, dynamic pivot table reporting system for any business task or function. Learning advanced pivot table and pivot chart techniques for Excel 2013 or the newest Office 365 has never been easier. You’ll find simple, step-by-step instructions, real-world case studies, even complete, easy recipes for solving your most common business analysis problems. • Create, customize, and change your pivot tables and pivot charts • Transform gigantic data sets into crystal-clear summary reports • Summarize and analyze data even faster with new Excel 2013 recommended pivot tables • Instantly highlight your most (and least) profitable customers, products, or regions • Quickly filter pivot tables using slicers • Use dynamic dashboards using Power View to see exactly where your business stands right now • Revamp analyses on the fly by simply dragging and dropping fields • Build dynamic self-service reporting systems your entire team can use • Use PowerPivot or the Data Model to create pivot tables from multiple data sources and worksheets • Work with and analyze OLAP data, and much more About MrExcel Library: Every book in the MrExcel Library pinpoints a specific set of crucial Excel tasks and presents focused skills and examples for performing them rapidly and effectively. Selected by Bill Jelen, Microsoft Excel MVP and mastermind behind the leading Excel solutions website MrExcel.com, these • Dramatically increase your productivity—saving you 50 hours a year or more • Present proven, creative strategies for solving real-world problems • Show you how to get great results, no matter how much data you have • Help you avoid critical mistakes that even experienced users make CATEGORY: Spreadsheets COVERS: Microsoft Office Excel 2013