Learn to use Excel dashboards and reports to better conceptualize data Updated for all the latest features and capabilities of Excel 2013, this go-to resource provides you with in-depth coverage of the individual functions and tools that can be used to create compelling Excel reports. Veteran author Michael Alexander walks you through the most effective ways to present and report data. Featuring a comprehensive review of a wide array of technical and analytical concepts, this essential guide helps you go from reporting data with simple tables full of dull numbers to presenting key information through the use of high-impact, meaningful reports and dashboards that will wow management both visually and substantively. Details how to analyze large amounts of data and report the results in a way that is both visually attractive and effective Describes how to use different perspectives to achieve better visibility into data, as well as how to slice data into various views on the fly Shows how to automate redundant reporting and analysis processes Walks you through creating impressive dashboards, eye-catching visualizations, and real-world What-If analyses Excel Dashboards and Reports, Second Edition is part technical manual, part analytical guidebook, and exactly what you need to become your organization's dashboard dynamo!

Statistical learning and analysis techniques have become extremely important today, given the tremendous growth in the size of heterogeneous data collections and the ability to process it even from physically distant locations. Recent advances made in the field of machine learning provide a strong framework for robust learning from the diverse corpora and continue to impact a variety of research problems across multiple scientific disciplines. The aim of this handbook is to familiarize beginners as well as experts with some of the recent techniques in this field. The Handbook is divided in two sections: Theory and Applications, covering machine learning, data analytics, biometrics, document recognition and security. very relevant to current research challenges faced in various fields self-contained reference to machine learning emphasis on applications-oriented techniques

Swarm Intelligence and bio-inspired computation have become increasing popular in the last two decades. Bio-inspired algorithms such as ant colony algorithms, bat algorithms, bee algorithms, firefly algorithms, cuckoo search and particle swarm optimization have been applied in almost every area of science and engineering with a dramatic increase of number of relevant publications. This book reviews the latest developments in swarm intelligence and bio-inspired computation from both the theory and application side, providing a complete resource that analyzes and discusses the latest and future trends in research directions. It can help new researchers to carry out timely research and inspire readers to develop new algorithms. With its impressive breadth and depth, this book will be useful for advanced undergraduate students, PhD students and lecturers in computer science, engineering and science as well as researchers and engineers. Focuses on the introduction and analysis of key algorithms Includes case studies for real-world applications Contains a balance of theory and applications, so readers who are interested in either algorithm or applications will all benefit from this timely book.

The smart way to learn Microsoft Visio 2013—one step at a time! Experience learning made easy—and quickly teach yourself how to create professional-looking business and technical diagrams with Visio 2013. With Step by Step, you set the pace—building and practicing the skills you need, just when you need them! Create dynamic organization charts with Visio Make charts with wizards or build them by hand Build drawings using Visio themes and effects Use data-driven drawings in Microsoft SharePoint Import, manipulate, and visualize business data Draw and then execute SharePoint 2013 workflows

Implementing Analytics demystifies the concept, technology and application of analytics and breaks its implementation down to repeatable and manageable steps, making it possible for widespread adoption across all functions of an organization. Implementing Analytics simplifies and helps democratize a very specialized discipline to foster business efficiency and innovation without investing in multi-million dollar technology and manpower. A technology agnostic methodology that breaks down complex tasks like model design and tuning and emphasizes business decisions rather than the technology behind analytics. Simplifies the understanding of analytics from a technical and functional perspective and shows a wide array of problems that can be tackled using existing technology Provides a detailed step by step approach to identify opportunities, extract requirements, design variables and build and test models. It further explains the business decision strategies to use analytics models and provides an overview for governance and tuning Helps formalize analytics projects from staffing, technology and implementation perspectives Emphasizes machine learning and data mining over statistics and shows how the role of a Data Scientist can be broken down and still deliver the value by building a robust development process

Introducing the tools of statistics and probability from the ground up An understanding of statistical tools is essential for engineers and scientists who often need to deal with data analysis over the course of their work. Statistics and Probability with Applications for Engineers and Scientists walks readers through a wide range of popular statistical techniques, explaining step-by-step how to generate, analyze, and interpret data for diverse applications in engineering and the natural sciences. Unique among books of this kind, Statistics and Probability with Applications for Engineers and Scientists covers descriptive statistics first, then goes on to discuss the fundamentals of probability theory. Along with case studies, examples, and real-world data sets, the book incorporates clear instructions on how to use the statistical packages Minitab and Microsoft Office Excel to analyze various data sets. The book also features: Detailed discussions on sampling distributions, statistical estimation of population parameters, hypothesis testing, reliability theory, statistical quality control including Phase I and Phase II control charts, and process capability indices A clear presentation of nonparametric methods and simple and multiple linear regression methods, as well as a brief discussion on logistic regression method Comprehensive guidance on the design of experiments, including randomized block designs, one- and two-way layout designs, Latin square designs, random effects and mixed effects models, factorial and fractional factorial designs, and response surface methodology A companion website containing data sets for Minitab and Microsoft Office Excel, as well as JMP routines and results Assuming no background in probability and statistics, Statistics and Probability with Applications for Engineers and Scientists features a unique, yet tried-and-true, approach that is ideal for all undergraduate students as well as statistical practitioners who analyze and illustrate real-world data in engineering and the natural sciences.

Celebrating the life of an admired pioneer in statistics In this captivating and inspiring memoir, world-renowned statistician George E. P. Box offers a firsthand account of his life and statistical work. Writing in an engaging, charming style, Dr. Box reveals the unlikely events that led him to a career in statistics, beginning with his job as a chemist conducting experiments for the British army during World War II. At this turning point in his life and career, Dr. Box taught himself the statistical methods necessary to analyze his own findings when there were no statisticians available to check his work. Throughout his autobiography, Dr. Box expertly weaves a personal and professional narrative to illustrate the effects his work had on his life and vice-versa. Interwoven between his research with time series analysis, experimental design, and the quality movement, Dr. Box recounts coming to the United States, his family life, and stories of the people who mean the most to him. This fascinating account balances the influence of both personal and professional relationships to demonstrate the extraordinary life of one of the greatest and most influential statisticians of our time. An Accidental Statistician also features: Two forewords written by Dr. Box's former colleagues and closest confidants Personal insights from more than a dozen statisticians on how Dr. Box has influenced and continues to touch their careers and lives Numerous, previously unpublished photos from the author's personal collection An Accidental Statistician is a compelling read for statisticians in education or industry, mathematicians, engineers, and anyone interested in the life story of an influential intellectual who altered the world of modern statistics.

Data simulation is a fundamental technique in statistical programming and research. Rick Wicklin's Simulating Data with SAS brings together the most useful algorithms and the best programming techniques for efficient data simulation in an accessible how-to book for practicing statisticians and statistical programmers.

This book discusses in detail how to simulate data from common univariate and multivariate distributions, and how to use simulation to evaluate statistical techniques. It also covers simulating correlated data, data for regression models, spatial data, and data with given moments. It provides tips and techniques for beginning programmers, and offers libraries of functions for advanced practitioners.

As the first book devoted to simulating data across a range of statistical applications, Simulating Data with SAS is an essential tool for programmers, analysts, researchers, and students who use SAS software.

This book is part of the SAS Press program.

JMP Start Statistics: A Guide to Statistics and Data Analysis Using JMP, Fifth Edition, is the perfect mix of software manual and statistics text. Authors John Sall, Ann Lehman, Mia Stephens, and Lee Creighton provide hands-on tutorials with just the right amount of conceptual and motivational material to illustrate how to use the intuitive interface for data analysis in JMP. Each chapter features concept-specific tutorials, examples, brief reviews of concepts, step-by-step illustrations, and exercises.

JMP Start Statistics, Fifth Edition, includes many new features of JMP 10, including an enhanced ability to manage a JMP session by easily tracking open and recently opened JMP tables; scripts, analyses, JMP projects, and other files; vastly expanded tools for instructors to demonstrate statistical concepts and interactive scripts to help students grasp difficult topics; Split-Plot designs with examples; examples of Graph Builder and Control Chart Builder; and new features that make the software easier to use.

This book is part of the SAS Press program.

This straightforward guide to PROC TEMPLATE shows you how to build your own custom styles and tables in SAS. You'll learn how to create new styles to match your organization's standards or simply to increase your report's aesthetic potential build custom tables with complex structures and traffic lighting to make them easier to read and interpret manage your templates and share them with other SAS users

Written for all levels of users, PROC TEMPLATE Made Easy guides you through the process of writing templates. Beginners will benefit from learning how to do so from the ground up. Intermediate and advanced users will learn the more complex features of PROC TEMPLATE as well as how to use styles in the Base SAS reporting procedures. This book explains how PROC TEMPLATE saves templates and teaches you how to create shareable template stores, allowing you to customize your working environment. The visual appendixes of all style attributes and graph colors serve as an essential reference for anyone using PROC TEMPLATE.

PROC TEMPLATE allows you to take advantage of all that the Output Delivery System has to offer, and PROC TEMPLATE Made Easy teaches you how.

This book is part of the SAS Press program.

Provides an introduction to the various statistical techniques involved in medical research and drug development with a focus on estimating the success probability of an experiment Success Probability Estimation with Applications to Clinical Trials details the use of success probability estimation in both the planning and analyzing of clinical trials and in widely used statistical tests. Devoted to both statisticians and non-statisticians who are involved in clinical trials, Part I of the book presents new concepts related to success probability estimation and their usefulness in clinical trials, and each section begins with a non-technical explanation of the presented concepts. Part II delves deeper into the techniques for success probability estimation and features applications to both reproducibility probability estimation and conservative sample size estimation. Success Probability Estimation with Applications to Clinical Trials: Addresses the theoretical and practical aspects of the topic and introduces new and promising techniques in the statistical and pharmaceutical industries Features practical solutions for problems that are often encountered in clinical trials Includes success probability estimation for widely used statistical tests, such as parametric and nonparametric models Focuses on experimental planning, specifically the sample size of clinical trials using phase II results and data for planning phase III trials Introduces statistical concepts related to success probability estimation and their usefulness in clinical trials Success Probability Estimation with Applications to Clinical Trials is an ideal reference for statisticians and biostatisticians in the pharmaceutical industry as well as researchers and practitioners in medical centers who are actively involved in health policy, clinical research, and the design and evaluation of clinical trials.

This handbook shows readers how best to manage and manipulate data by using the DATA step in SAS, helping them avoid common problems when creating SAS data sets. The author explains that learning syntax does not solve all problems; rather, a thorough comprehension of SAS processing is needed for successful programming.

This book covers the basics of how to explore data and build reports using SAS Visual Analytics. The emphasis is on introductory instructions, how-to hints, and quick reference information.

A UNIQUE ENGINEERING AND STATISTICAL APPROACH TO OPTIMAL RESOURCE ALLOCATION Optimal Resource Allocation: With Practical Statistical Applications and Theory features the application of probabilistic and statistical methods used in reliability engineering during the different phases of life cycles of technical systems. Bridging the gap between reliability engineering and applied mathematics, the book outlines different approaches to optimal resource allocation and various applications of models and algorithms for solving real-world problems. In addition, the fundamental background on optimization theory and various illustrative numerical examples are provided. The book also features: An overview of various approaches to optimal resource allocation, from classical Lagrange methods to modern algorithms based on ideas of evolution in biology Numerous exercises and case studies from a variety of areas, including communications, transportation, energy transmission, and counterterrorism protection The applied methods of optimization with various methods of optimal redundancy problem solutions as well as the numerical examples and statistical methods needed to solve the problems Practical thoughts, opinions, and judgments on real-world applications of reliability theory and solves practical problems using mathematical models and algorithms Optimal Resource Allocation is a must-have guide for electrical, mechanical, and reliability engineers dealing with engineering design and optimal reliability problems. In addition, the book is excellent for graduate and PhD-level courses in reliability theory and optimization.

A new edition of the definitive guide to logistic regression modeling for health science and other applications This thoroughly expanded Third Edition provides an easily accessible introduction to the logistic regression (LR) model and highlights the power of this model by examining the relationship between a dichotomous outcome and a set of covariables. Applied Logistic Regression, Third Edition emphasizes applications in the health sciences and handpicks topics that best suit the use of modern statistical software. The book provides readers with state-of-the-art techniques for building, interpreting, and assessing the performance of LR models. New and updated features include: A chapter on the analysis of correlated outcome data A wealth of additional material for topics ranging from Bayesian methods to assessing model fit Rich data sets from real-world studies that demonstrate each method under discussion Detailed examples and interpretation of the presented results as well as exercises throughout Applied Logistic Regression, Third Edition is a must-have guide for professionals and researchers who need to model nominal or ordinal scaled outcome variables in public health, medicine, and the social sciences as well as a wide range of other fields and disciplines.

Anders Milhøj's Practical Time Series Analysis Using SAS explains and demonstrates through examples how you can use SAS for time series analysis. It offers modern procedures for forecasting, seasonal adjustments, and decomposition of time series that can be used without involved statistical reasoning. The book teaches, with numerous examples, how to apply these procedures with very simple coding. In addition, it also gives the statistical background for interested readers. Beginning with an introductory chapter that covers the practical handling of time series data in SAS using the TIMESERIES and EXPAND procedures, it goes on to explain forecasting, which is found in the ESM procedure; seasonal adjustment, including trading-day correction using PROC X12; and unobserved component models using the UCM procedure.

This book is part of the SAS Press program.

Take the mystery out of statistical terms and put Excel to work! If you need to create and interpret statistics in business or classroom settings, this easy-to-use guide is just what you need. It shows you how to use Excel's powerful tools for statistical analysis, even if you've never taken a course in statistics. Learn the meaning of terms like mean and median, margin of error, standard deviation, and permutations, and discover how to interpret the statistics of everyday life. You'll learn to use Excel formulas, charts, PivotTables, and other tools to make sense of everything from sports stats to medical correlations. Statistics have a reputation for being challenging and math-intensive; this friendly guide makes statistical analysis with Excel easy to understand Explains how to use Excel to crunch numbers and interpret the statistics of everyday life: sales figures, gambling odds, sports stats, a grading curve, and much more Covers formulas and functions, charts and PivotTables, samples and normal distributions, probabilities and related distributions, trends, and correlations Clarifies statistical terms such as median vs. mean, margin of error, standard deviation, correlations, and permutations Statistical Analysis with Excel For Dummies, 3rd Edition helps you make sense of statistics and use Excel's statistical analysis tools in your daily life.

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.