Data Table Sensitivity Analysis

  data table sensitivity analysis: Sensitivity Analysis in Practice Andrea Saltelli, Stefano Tarantola, Francesca Campolongo, Marco Ratto, 2004-07-16 Sensitivity analysis should be considered a pre-requisite for statistical model building in any scientific discipline where modelling takes place. For a non-expert, choosing the method of analysis for their model is complex, and depends on a number of factors. This book guides the non-expert through their problem in order to enable them to choose and apply the most appropriate method. It offers a review of the state-of-the-art in sensitivity analysis, and is suitable for a wide range of practitioners. It is focussed on the use of SIMLAB – a widely distributed freely-available sensitivity analysis software package developed by the authors – for solving problems in sensitivity analysis of statistical models. Other key features: Provides an accessible overview of the current most widely used methods for sensitivity analysis. Opens with a detailed worked example to explain the motivation behind the book. Includes a range of examples to help illustrate the concepts discussed. Focuses on implementation of the methods in the software SIMLAB - a freely-available sensitivity analysis software package developed by the authors. Contains a large number of references to sources for further reading. Authored by the leading authorities on sensitivity analysis.
  data table sensitivity analysis: Developing a Protocol for Observational Comparative Effectiveness Research: A User's Guide Agency for Health Care Research and Quality (U.S.), 2013-02-21 This User’s Guide is a resource for investigators and stakeholders who develop and review observational comparative effectiveness research protocols. It explains how to (1) identify key considerations and best practices for research design; (2) build a protocol based on these standards and best practices; and (3) judge the adequacy and completeness of a protocol. Eleven chapters cover all aspects of research design, including: developing study objectives, defining and refining study questions, addressing the heterogeneity of treatment effect, characterizing exposure, selecting a comparator, defining and measuring outcomes, and identifying optimal data sources. Checklists of guidance and key considerations for protocols are provided at the end of each chapter. The User’s Guide was created by researchers affiliated with AHRQ’s Effective Health Care Program, particularly those who participated in AHRQ’s DEcIDE (Developing Evidence to Inform Decisions About Effectiveness) program. Chapters were subject to multiple internal and external independent reviews. More more information, please consult the Agency website: www.effectivehealthcare.ahrq.gov)
  data table sensitivity analysis: Global Sensitivity Analysis Andrea Saltelli, Marco Ratto, Terry Andres, Francesca Campolongo, Jessica Cariboni, Debora Gatelli, Michaela Saisana, Stefano Tarantola, 2008-02-28 Complex mathematical and computational models are used in all areas of society and technology and yet model based science is increasingly contested or refuted, especially when models are applied to controversial themes in domains such as health, the environment or the economy. More stringent standards of proofs are demanded from model-based numbers, especially when these numbers represent potential financial losses, threats to human health or the state of the environment. Quantitative sensitivity analysis is generally agreed to be one such standard. Mathematical models are good at mapping assumptions into inferences. A modeller makes assumptions about laws pertaining to the system, about its status and a plethora of other, often arcane, system variables and internal model settings. To what extent can we rely on the model-based inference when most of these assumptions are fraught with uncertainties? Global Sensitivity Analysis offers an accessible treatment of such problems via quantitative sensitivity analysis, beginning with the first principles and guiding the reader through the full range of recommended practices with a rich set of solved exercises. The text explains the motivation for sensitivity analysis, reviews the required statistical concepts, and provides a guide to potential applications. The book: Provides a self-contained treatment of the subject, allowing readers to learn and practice global sensitivity analysis without further materials. Presents ways to frame the analysis, interpret its results, and avoid potential pitfalls. Features numerous exercises and solved problems to help illustrate the applications. Is authored by leading sensitivity analysis practitioners, combining a range of disciplinary backgrounds. Postgraduate students and practitioners in a wide range of subjects, including statistics, mathematics, engineering, physics, chemistry, environmental sciences, biology, toxicology, actuarial sciences, and econometrics will find much of use here. This book will prove equally valuable to engineers working on risk analysis and to financial analysts concerned with pricing and hedging.
  data table sensitivity analysis: Missing Data in Longitudinal Studies Michael J. Daniels, Joseph W. Hogan, 2008-03-11 Drawing from the authors' own work and from the most recent developments in the field, Missing Data in Longitudinal Studies: Strategies for Bayesian Modeling and Sensitivity Analysis describes a comprehensive Bayesian approach for drawing inference from incomplete data in longitudinal studies. To illustrate these methods, the authors employ
  data table sensitivity analysis: Next Generation Excel Isaac Gottlieb, 2013-02-04 Take Excel to the next level in accounting and financial modeling In this new Second Edition of Next Generation Excel, Isaac Gottlieb shows financial analysts how to harness the full power of Excel to move forward into the new world of accounting and finance. Companies of all sizes use financial models to analyze their finances and plan business operations, as well as to create financial accounting reports like balance sheets, income statements, and statements of cash flows. While many businesspeople are quite familiar with the reports created with financial models, most are not as familiar with the creation of the models themselves. This book shows them how to build an accurate and effective financial model using the solid functionality and easy usability of Excel. Fully updated and revised to include support for Apple users Written by a professor of management and statistics who has taught the discipline for fifteen years Appropriate for professional financial analysts, as well as MBA students For professionals and students whose responsibilities or studies include a full understanding of financial modeling, Next Generation Excel, Second Edition offers comprehensive training.
  data table sensitivity analysis: Sensitivity Analysis in Earth Observation Modelling George P. Petropoulos, Prashant K. Srivastava, 2016-10-07 Sensitivity Analysis in Earth Observation Modeling highlights the state-of-the-art in ongoing research investigations and new applications of sensitivity analysis in earth observation modeling. In this framework, original works concerned with the development or exploitation of diverse methods applied to different types of earth observation data or earth observation-based modeling approaches are included. An overview of sensitivity analysis methods and principles is provided first, followed by examples of applications and case studies of different sensitivity/uncertainty analysis implementation methods, covering the full spectrum of sensitivity analysis techniques, including operational products. Finally, the book outlines challenges and future prospects for implementation in earth observation modeling. Information provided in this book is of practical value to readers looking to understand the principles of sensitivity analysis in earth observation modeling, the level of scientific maturity in the field, and where the main limitations or challenges are in terms of improving our ability to implement such approaches in a wide range of applications. Readers will also be informed on the implementation of sensitivity/uncertainty analysis on operational products available at present, on global and continental scales. All of this information is vital in the selection process of the most appropriate sensitivity analysis method to implement. - Outlines challenges and future prospects of sensitivity analysis implementation in earth observation modeling - Provides readers with a roadmap for directing future efforts - Includes case studies with applications from different regions around the globe, helping readers to explore strengths and weaknesses of the different methods in earth observation modeling - Presents a step-by-step guide, providing the principles of each method followed by the application of variants, making the reference easy to use and follow
  data table sensitivity analysis: The Prevention and Treatment of Missing Data in Clinical Trials National Research Council, Division of Behavioral and Social Sciences and Education, Committee on National Statistics, Panel on Handling Missing Data in Clinical Trials, 2010-12-21 Randomized clinical trials are the primary tool for evaluating new medical interventions. Randomization provides for a fair comparison between treatment and control groups, balancing out, on average, distributions of known and unknown factors among the participants. Unfortunately, these studies often lack a substantial percentage of data. This missing data reduces the benefit provided by the randomization and introduces potential biases in the comparison of the treatment groups. Missing data can arise for a variety of reasons, including the inability or unwillingness of participants to meet appointments for evaluation. And in some studies, some or all of data collection ceases when participants discontinue study treatment. Existing guidelines for the design and conduct of clinical trials, and the analysis of the resulting data, provide only limited advice on how to handle missing data. Thus, approaches to the analysis of data with an appreciable amount of missing values tend to be ad hoc and variable. The Prevention and Treatment of Missing Data in Clinical Trials concludes that a more principled approach to design and analysis in the presence of missing data is both needed and possible. Such an approach needs to focus on two critical elements: (1) careful design and conduct to limit the amount and impact of missing data and (2) analysis that makes full use of information on all randomized participants and is based on careful attention to the assumptions about the nature of the missing data underlying estimates of treatment effects. In addition to the highest priority recommendations, the book offers more detailed recommendations on the conduct of clinical trials and techniques for analysis of trial data.
  data table sensitivity analysis: Sensitivity Analysis Andrea Saltelli, K. Chan, E. M. Scott, 2009-03-16 The Wiley Paperback Series makes valuable content more accessible to a new generation of statisticians, mathematicians and scientists. Sensitivity analysis is used to ascertain how a given model output depends upon the input parameters. This is an important method for checking the quality of a given model, as well as a powerful tool for checking the robustness and reliability of its analysis. The topic is acknowledged as essential for good modelling practice and is an implicit part of any modelling field. Offers an accessible introduction to sensitivity analysis. Covers all the latest research. Illustrates concepts with numerous examples, applications and case studies. Includes contributions from the leading researchers active in developing strategies for sensitivity analysis. The principles of sensitivity analysis are carefully described and suitable methods for approaching many types of problems are given. The book introduces the modeller to the entire casual assessment chain, from data to predictions, whilst explaining the impact of source uncertainties and framing assumptions. A ‘hitch-hikers guide’ is included to allow the more experienced reader to readily access specific applications. Modellers from a wide range of disciplines, including biostatistics, economics, environmental impact assessment, chemistry and engineering will benefit greatly from the numerous examples and applications. Presents many different sensitivity analysis methodologies and demonstrates their usefulness in scientific research. (Zentralblatt MATH)
  data table sensitivity analysis: Sensitivity Analysis: Matrix Methods in Demography and Ecology Hal Caswell, 2019-04-02 This open access book shows how to use sensitivity analysis in demography. It presents new methods for individuals, cohorts, and populations, with applications to humans, other animals, and plants. The analyses are based on matrix formulations of age-classified, stage-classified, and multistate population models. Methods are presented for linear and nonlinear, deterministic and stochastic, and time-invariant and time-varying cases. Readers will discover results on the sensitivity of statistics of longevity, life disparity, occupancy times, the net reproductive rate, and statistics of Markov chain models in demography. They will also see applications of sensitivity analysis to population growth rates, stable population structures, reproductive value, equilibria under immigration and nonlinearity, and population cycles. Individual stochasticity is a theme throughout, with a focus that goes beyond expected values to include variances in demographic outcomes. The calculations are easily and accurately implemented in matrix-oriented programming languages such as Matlab or R. Sensitivity analysis will help readers create models to predict the effect of future changes, to evaluate policy effects, and to identify possible evolutionary responses to the environment. Complete with many examples of the application, the book will be of interest to researchers and graduate students in human demography and population biology. The material will also appeal to those in mathematical biology and applied mathematics.
  data table sensitivity analysis: Flexible Imputation of Missing Data, Second Edition Stef van Buuren, 2018-07-17 Missing data pose challenges to real-life data analysis. Simple ad-hoc fixes, like deletion or mean imputation, only work under highly restrictive conditions, which are often not met in practice. Multiple imputation replaces each missing value by multiple plausible values. The variability between these replacements reflects our ignorance of the true (but missing) value. Each of the completed data set is then analyzed by standard methods, and the results are pooled to obtain unbiased estimates with correct confidence intervals. Multiple imputation is a general approach that also inspires novel solutions to old problems by reformulating the task at hand as a missing-data problem. This is the second edition of a popular book on multiple imputation, focused on explaining the application of methods through detailed worked examples using the MICE package as developed by the author. This new edition incorporates the recent developments in this fast-moving field. This class-tested book avoids mathematical and technical details as much as possible: formulas are accompanied by verbal statements that explain the formula in accessible terms. The book sharpens the reader’s intuition on how to think about missing data, and provides all the tools needed to execute a well-grounded quantitative analysis in the presence of missing data.
  data table sensitivity analysis: Excel Data Analysis Hector Guerrero, 2018-12-14 This book offers a comprehensive and readable introduction to modern business and data analytics. It is based on the use of Excel, a tool that virtually all students and professionals have access to. The explanations are focused on understanding the techniques and their proper application, and are supplemented by a wealth of in-chapter and end-of-chapter exercises. In addition to the general statistical methods, the book also includes Monte Carlo simulation and optimization. The second edition has been thoroughly revised: new topics, exercises and examples have been added, and the readability has been further improved. The book is primarily intended for students in business, economics and government, as well as professionals, who need a more rigorous introduction to business and data analytics – yet also need to learn the topic quickly and without overly academic explanations.
  data table sensitivity analysis: Prescriptive Analytics Jeffrey M. Keisler,
  data table sensitivity analysis: Building Financial Models with Microsoft Excel K. Scott Proctor, 2004-10-28 A comprehensive guide to building financial models Building Financial Models with Microsoft Excel + CD-ROM provides beginning or intermediate level computer users with step-by-step instructions on building financial models using Microsoft Excel-the most popular spreadsheet program available. The accompanying CD-ROM contains Excel worksheets that track the course of the book and allow readers to build their own financial models. This comprehensive resource also covers important topics such as the concept of valuation, the concept of sensitivity analysis, the concepts of contribution margin and financial ratios and the basics of building and using a Capitalization Table. K. Scott Proctor, CFA, is the Director of Investor Analytics at SNL Financial, a financial information provider.
  data table sensitivity analysis: Sensitivity Analysis Emanuele Borgonovo, 2017-04-19 This book is an expository introduction to the methodology of sensitivity analysis of model output. It is primarily intended for investigators, students and researchers that are familiar with mathematical models but are less familiar with the techniques for performing their sensitivity analysis. A variety of sensitivity methods have been developed over the years. This monograph helps the analyst in her/his first exploration of this world. The main goal is to foster the recognition of the crucial role of sensitivity analysis methods as the techniques that allow us to gain insights from quantitative models. Also, exercising rigor in performing sensitivity analysis becomes increasingly relevant both to decision makers and modelers. The book helps the analyst in structuring her/his sensitivity analysis quest properly, so as to obtain the correct answer to the corresponding managerial question. The first part of the book covers Deterministic Methods, including Tornado Diagrams; One-Way Sensitivity Analysis; Differentiation-Based Methods and Local Sensitivity Analysis with Constraints. The second part looks at Probabilistic Methods, including Regression-Based methods, Variance-Based Methods, and Distribution-Based methods. The final section looks at Applications, including capital budgeting, sensitivity analysis in climate change modelling and in the risk assessment of a lunar space mission.
  data table sensitivity analysis: Excel 2010 Workbook For Dummies Greg Harvey, 2010-08-13 Reinforce your understanding of Excel with these Workbook exercises Boost your knowledge of important Excel tasks by putting your skills to work in real-world situations. The For Dummies Workbook format provides more than 100 exercises that help you create actual results with Excel so you can gain proficiency. Perfect for students, people learning Excel on their own, and financial professionals who must plan and execute complex projects in Excel, Excel 2010 Workbook For Dummies helps you discover all the ways this program can work for you. Excel is the world's most popular number-crunching program, and For Dummies books are the most popular guides to Excel The Workbook approach offers practical application, with more than 100 exercises to work through and plenty of step-by-step guidance This guide covers the new features of Excel 2010, includes a section on creating graphic displays of information, and offers ideas for financial planners Also provides exercises on using formulas and functions, managing and securing data, and performing data analysis A companion CD-ROM includes screen shots and practice materials Excel 2010 Workbook For Dummies helps you get comfortable with Excel so you can take advantage of all it has to offer. Note: CD-ROM/DVD and other supplementary materials are not included as part of eBook file.
  data table sensitivity analysis: Microsoft Excel Data Analysis and Business Modeling Wayne Winston, 2016-11-29 This is the eBook of the printed book and may not include any media, website access codes, or print supplements that may come packaged with the bound book. Master business modeling and analysis techniques with Microsoft Excel 2016, and transform data into bottom-line results. Written by award-winning educator Wayne Winston, this hands on, scenario-focused guide helps you use Excel’s newest tools to ask the right questions and get accurate, actionable answers. This edition adds 150+ new problems with solutions, plus a chapter of basic spreadsheet models to make sure you’re fully up to speed. Solve real business problems with Excel–and build your competitive advantage Quickly transition from Excel basics to sophisticated analytics Summarize data by using PivotTables and Descriptive Statistics Use Excel trend curves, multiple regression, and exponential smoothing Master advanced functions such as OFFSET and INDIRECT Delve into key financial, statistical, and time functions Leverage the new charts in Excel 2016 (including box and whisker and waterfall charts) Make charts more effective by using Power View Tame complex optimizations by using Excel Solver Run Monte Carlo simulations on stock prices and bidding models Work with the AGGREGATE function and table slicers Create PivotTables from data in different worksheets or workbooks Learn about basic probability and Bayes’ Theorem Automate repetitive tasks by using macros
  data table sensitivity analysis: Sensitivity Analysis in Linear Regression Samprit Chatterjee, Ali S. Hadi, 2009-09-25 Treats linear regression diagnostics as a tool for application of linear regression models to real-life data. Presentation makes extensive use of examples to illustrate theory. Assesses the effect of measurement errors on the estimated coefficients, which is not accounted for in a standard least squares estimate but is important where regression coefficients are used to apportion effects due to different variables. Also assesses qualitatively and numerically the robustness of the regression fit.
  data table sensitivity analysis: Tips & Tricks for Excel-Based Financial Modeling, Volume II M.A. Mian, 2017-07-31 The purpose of this work is to show some advanced concepts related to Excel based financial modelling. Microsoft ExcelTM is a very powerful tool and most of the time we do not utilize its full potential. Of course, any advanced concepts require the basic knowledge which most of us have and then build on it. It is only by hands-on experimentation that one learns the art of constructing an efficient worksheet. The two volumes of this book cover dynamic charting, macros, goal seek, solver, the routine Excel functions commonly used, the lesser known Excel functions, the Excel’s financial functions and so on. The introduction of macros in these books is not exhaustive but the purpose of what is presented is to show you the power of Excel and how it can be utilized to automate most repetitive calculations at a click of a button. For those who use Excel on a daily basis in financial modeling and project/investment evaluations, this book is a must.
  data table sensitivity analysis: Estimands, Estimators and Sensitivity Analysis in Clinical Trials Craig Mallinckrodt, Geert Molenberghs, Ilya Lipkovich, Bohdana Ratitch, 2019-12-23 The concepts of estimands, analyses (estimators), and sensitivity are interrelated. Therefore, great need exists for an integrated approach to these topics. This book acts as a practical guide to developing and implementing statistical analysis plans by explaining fundamental concepts using accessible language, providing technical details, real-world examples, and SAS and R code to implement analyses. The updated ICH guideline raises new analytic and cross-functional challenges for statisticians. Gaps between different communities have come to surface, such as between causal inference and clinical trialists, as well as among clinicians, statisticians, and regulators when it comes to communicating decision-making objectives, assumptions, and interpretations of evidence. This book lays out a path toward bridging some of these gaps. It offers  A common language and unifying framework along with the technical details and practical guidance to help statisticians meet the challenges  A thorough treatment of intercurrent events (ICEs), i.e., postrandomization events that confound interpretation of outcomes and five strategies for ICEs in ICH E9 (R1)  Details on how estimands, integrated into a principled study development process, lay a foundation for coherent specification of trial design, conduct, and analysis needed to overcome the issues caused by ICEs:  A perspective on the role of the intention-to-treat principle  Examples and case studies from various areas  Example code in SAS and R  A connection with causal inference  Implications and methods for analysis of longitudinal trials with missing data Together, the authors have offered the readers their ample expertise in clinical trial design and analysis, from an industrial and academic perspective.
  data table sensitivity analysis: Introductory Financial Economics with Spreadsheets Cornelis van de Panne, 2020-08-13 This text combines the teaching and explanation of spreadsheets with the essentials of finance and economics in a highly-visual, interactive and project-based approach. Students progressively build skills in Microsoft Excel, by proceeding through a variety of basic applications. Users of other spreadsheets will also benefit from the book. This innovative publication includes an accompanying disk that provides the spreadsheet files on which the text is based and the data for the exercises and assignments following each chapter.
  data table sensitivity analysis: Introduction to Financial Models for Management and Planning James R. Morris, John P. Daley, 2017-05-30 A properly structured financial model can provide decision makers with a powerful planning tool that helps them identify the consequences of their decisions before they are put into practice. Introduction to Financial Models for Management and Planning, Second Edition enables professionals and students to learn how to develop and use computer-based models for financial planning. This volume provides critical tools for the financial toolbox, then shows how to use them tools to build successful models.
  data table sensitivity analysis: Decision Support, Analytics, and Business Intelligence, Third Edition Daniel J. Power, Ciara Heavin, 2017-06-08 Rapid technology change is impacting organizations large and small. Mobile and Cloud computing, the Internet of Things (IoT), and “Big Data” are driving forces in organizational digital transformation. Decision support and analytics are available to many people in a business or organization. Business professionals need to learn about and understand computerized decision support for organizations to succeed. This text is targeted to busy managers and students who need to grasp the basics of computerized decision support, including: What is analytics? What is a decision support system? What is “Big Data”? What are “Big Data” business use cases? Overall, it addresses 61 fundamental questions. In a short period of time, readers can “get up to speed” on decision support, analytics, and business intelligence. The book then provides a quick reference to important recurring questions.
  data table sensitivity analysis: Excel 2022 Pro 100 + PivotTables, Charts & Reports Dr. Isaac Gottlieb, 2022-11-04 Learn Everything about Excel Charts, PivotTables, Dashboards and Master Analytic Techniques for Decision Making DESCRIPTION Excel's charts, graphs, and reports are beneficial, so it's time to use them to your advantage. Learn how to execute the most innovative analysis on your preferred data using PivotTables, PivotCharts, What-if-Analysis, descriptive statistics, correlations, histograms, sparklines, animated charts, dashboards, trendlines, and more than 100 other charts and graphs. The book includes the following: ● Try and practice new Excel 2022 Charts and Reports in your Excel 2019, Excel 2021 and Office 365 editions. ● Learn with easy-to-read, step-by-step instructions and screenshots. ● Learn to illustrate your data in a way that is readily digestible at a glance. ● Figure out how to make beautiful infographics that reflect your company's personality or culture. ● Learn the ins and outs of making and editing expert PivotTables and PivotCharts. ● Master PivotTables and PivotCharts to construct dynamic dashboards. ● Utilize Excel's What-If analysis to check your assumptions and theories. ● Create Sensitivity-Analysis tables to check the quality of your decision-making tools. ● Create summaries, cross-tabs, filtering, and other visualizations. ● Conduct in-depth statistical analysis in Excel with minimal effort. This book's thorough instructions on Excel charts will improve readers' skills in making the most innovative and visually appealing reports. You will be able to make dynamic, eye-catching dashboards once you complete reading this book. WHO THIS BOOK IS FOR No matter what your professional or academic status is, if you often engage in data analysis, summary creation, and report writing, this book is for you. You'll be able to generate relatively strong reports and infographics from your data, thereby allowing you to make more well-informed decisions. There is no need for you to be an Excel expert to use this book. TABLE OF CONTENTS Part I 1. Selecting Various Charts and Graphs 2. Chart Elements, Styles, and Analysis 3. Custom Charts, Data Filtering, and Formatting 4. Animations, Sparklines, and Conditional Formatting Part II 5. Speed Up with PivotTables 6. Preparing and Labeling PivotTable Source Data 7. Create, Calculate, and Format PivotTables 8. Sort, Filter, and Group PivotTables 9. PivotTables Calculations, Formulas, and Functions 10. PivotCharts 11. PivotTable Slicers and Timelines 12. PivotTable Dashboards 13. Charts and PivotTable Case Studies Part III 14. Descriptive Statistics, Correlation, and Histograms 15. Goal Seek and Sensitivity Analysis
  data table sensitivity analysis: Using Excel for Business and Financial Modelling Danielle Stein Fairhurst, 2019-03-25 A hands-on guide to using Excel in the business context First published in 2012, Using Excel for Business and Financial Modelling contains step-by-step instructions of how to solve common business problems using financial models, including downloadable Excel templates, a list of shortcuts and tons of practical tips and techniques you can apply straight away. Whilst there are many hundreds of tools, features and functions in Excel, this book focuses on the topics most relevant to finance professionals. It covers these features in detail from a practical perspective, but also puts them in context by applying them to practical examples in the real world. Learn to create financial models to help make business decisions whilst applying modelling best practice methodology, tools and techniques. • Provides the perfect mix of practice and theory • Helps you become a DIY Excel modelling specialist • Includes updates for Excel 2019/365 and Excel for Mac • May be used as an accompaniment to the author’s online and face-to-face training courses Many people are often overwhelmed by the hundreds of tools in Excel, and this book gives clarity to the ones you need to know in order to perform your job more efficiently. This book also demystifies the technical, design, logic and financial skills you need for business and financial modelling.
  data table sensitivity analysis: Microsoft Excel 2013 Data Analysis and Business Modeling Wayne Winston, 2014-01-15 Master business modeling and analysis techniques with Microsoft Excel 2013, and transform data into bottom-line results. Written by award-winning educator Wayne Winston, this hands-on, scenario-focused guide shows you how to use the latest Excel tools to integrate data from multiple tables—and how to effectively build a relational data source inside an Excel workbook. Solve real business problems with Excel—and sharpen your edge Summarize data with PivotTables and Descriptive Statistics Explore new trends in predictive and prescriptive analytics Use Excel Trend Curves, multiple regression, and exponential smoothing Master advanced Excel functions such as OFFSET and INDIRECT Delve into key financial, statistical, and time functions Make your charts more effective with the Power View tool Tame complex optimization problems with Excel Solver Run Monte Carlo simulations on stock prices and bidding models Apply important modeling tools such as the Inquire add-in
  data table sensitivity analysis: Decision Making in Systems Engineering and Management Gregory S. Parnell, Patrick J. Driscoll, Dale L. Henderson, 2011-03-16 Decision Making in Systems Engineering and Management is a comprehensive textbook that provides a logical process and analytical techniques for fact-based decision making for the most challenging systems problems. Grounded in systems thinking and based on sound systems engineering principles, the systems decisions process (SDP) leverages multiple objective decision analysis, multiple attribute value theory, and value-focused thinking to define the problem, measure stakeholder value, design creative solutions, explore the decision trade off space in the presence of uncertainty, and structure successful solution implementation. In addition to classical systems engineering problems, this approach has been successfully applied to a wide range of challenges including personnel recruiting, retention, and management; strategic policy analysis; facilities design and management; resource allocation; information assurance; security systems design; and other settings whose structure can be conceptualized as a system.
  data table sensitivity analysis: Using Excel for Business Analysis Danielle Stein Fairhurst, 2015-03-17 Utilise Excel 2013 capabilities to build effective financial models Using Excel for Business Analysis, Revised Edition provides practical guidance for anyone looking to build financial models. Whether for business proposals, opportunity evaluation, financial reports, or any other business finance application, this book shows you how to design, create, and test your model, then present your results effectively using Excel 2013. The book opens with a general guide to financial modelling, with each subsequent chapter building skill upon skill until you have a real, working model of your own. Financial tools, features, and functions are covered in detail from a practical perspective, and put in context with application to real-world examples. Each chapter focuses on a different aspect of Excel modelling, including step-by-step instructions that walk you through each feature, and the companion website provides live model worksheets that give you the real hands-on practice you need to start doing your job faster, more efficiently, and with fewer errors. Financial modelling is an invaluable business tool, and Excel 2013 is capable of supporting the most common and useful models most businesses need. This book shows you how to dig deeper into Excel's functionality to craft effective financial models and provide important information that informs good decision-making. Learn financial modelling techniques and best practice Master the formulas and functions that bring your model to life Apply stress testing and sensitivity analysis with advanced conditionals Present your results effectively, whether graphically, orally, or written A deceptively powerful application, Excel supports many hundreds of tools, features, and functions; Using Excel for Business Analysis eliminates the irrelevant to focus on those that are most useful to business finance users, with detailed guidance toward utilisation and best practice.
  data table sensitivity analysis: Microsoft Excel Professional 2021 Guide CA Manmeet Singh Mehta, 2022-09-13 The power to build a successful career is at your fingertips with Excel 2021 DESCRIPTION Do you struggle with handling Excel data? Do you waste a lot of time figuring out which formulas and functions to use for your day-to-day office work? Even so, do you still want to become a master of Excel's most advanced features and techniques? This book will teach you the fundamentals and most beneficial uses of Microsoft Excel through various examples, practical illustrations, and good shortcuts to make your life easier with it. To begin, we'll look at the numerous features every professional needs to manage enormous volumes of data. The reader will discover how to import data from various sources and cleanse and arrange it. You'll learn how to use Excel's formulas and functions, as well as how to analyse data in a variety of ways. This book will demonstrate how Excel's new capabilities combine AI and ML to improve and simplify data visualisation straightforwardly. This book will teach you how to solve business problems using Excel's built-in functions. In this book, you will learn: ● Start with the essential Excel skills and gradually learn the sophisticated formulas. ● Discover how to quickly and easily import data from various external sources and formats. ● Eliminate complex data structures, adjust formats, and enhance data visibility. ● Discover hundreds of shortcuts, do complex computations, and study intelligent visuals. ● Learn how to use PivotTables, What-If Analysis and Array functions to generate valuable reports and dashboards. What makes this book your go-to Excel skill guide? ● Excel techniques and formulas. ● Several practical examples that make day-to-day job activities easier in minutes. ● With only a few clicks, you can learn to filter, manage, and analyse your business data. ● High-quality images and screenshots help you choose the correct tool in seconds. And there are many more to explore in this book. WHO THIS BOOK IS FOR Students, recent graduates, and professionals, such as Accountants, Retail Managers, Sales Executives, Business Analysts, Administrative Assistants, and HR Professionals who want to boost their day-to-day data management and analytical skills, will find this book to be an invaluable resource. This book, along with Excel or Microsoft 365, is all you need to become a professional Excel user. TABLE OF CONTENTS 1. What is New in Excel 2021 2. Excel Basics 3. Transforming and Managing Data 4. Achieving Data Consistency 5. Manipulating data 6. Power of Tables 7. Introduction to Formulas and Functions 8. Text & Other Functions 9. Date Functions 10. Logical and Lookup Functions 11. Array Functions 12. Formula Auditing 13. PivotTables 14. What-If Analysis 15. Protection and Security 16. Conditional Formatting 17. Charting Data 18. Excel Hacks and Tips - The Practical Side 19. The Way Forward
  data table sensitivity analysis: Microsoft Excel Data Analysis and Business Modeling (Office 2021 and Microsoft 365) Wayne Winston, 2021-12-17 Master business modeling and analysis techniques with Microsoft Excel and transform data into bottom-line results. Award-winning educator Wayne Winston's hands-on, scenario-focused guide helps you use today's Excel to ask the right questions and get accurate, actionable answers. More extensively updated than any previous edition, new coverage ranges from one-click data analysis to STOCKHISTORY, dynamic arrays to Power Query, and includes six new chapters. Practice with over 900 problems, many based on real challenges faced by working analysts. Solve real problems with Microsoft Excel—and build your competitive advantage Quickly transition from Excel basics to sophisticated analytics Use recent Power Query enhancements to connect, combine, and transform data sources more effectively Use the LAMBDA and LAMBDA helper functions to create Custom Functions without VBA Use New Data Types to import data including stock prices, weather, information on geographic areas, universities, movies, and music Build more sophisticated and compelling charts Use the new XLOOKUP function to revolutionize your lookup formulas Master new Dynamic Array formulas that allow you to sort and filter data with formulas and find all UNIQUE entries Illuminate insights from geographic and temporal data with 3D Maps Improve decision-making with probability, Bayes' theorem, and Monte Carlo simulation and scenarios Use Excel trend curves, multiple regression, and exponential smoothing for predictive analytics Use Data Model and Power Pivot to effectively build and use relational data sources inside an Excel workbook
  data table sensitivity analysis: Applications of Activated Sludge Models Damir Brdjanovic, S. C. F. Meijer, C. M. Lopez-Vazquez, C. M. Hooijmans, Mark C. M. van Loosdrecht, 2015-02-15 In 1982 the International Association on Water Pollution Research and Control (IAWPRC), as it was then called, established a Task Group on Mathematical Modelling for Design and Operation of Activated Sludge Processes. The aim of the Task Group was to create a common platform that could be used for the future development of models for COD and N removal with a minimum of complexity. As the collaborative result of the work of several modelling groups, the Activated Sludge Model No. 1 (ASM1) was published in 1987, exactly 25 years ago. The ASM1 can be considered as the reference model, since this model triggered the general acceptance of wastewater treatment modelling, first in the research community and later on also in practice. ASM1 has become a reference for many scientific and practical projects, and has been implemented (in some cases with modifications) in most of the commercial software available for modelling and simulation of plants for N removal. The models have grown more complex over the years, from ASM1, including N removal processes, to ASM2 (and its variations) including P removal processes, and ASM3 that corrects the deficiencies of ASM1 and is based on a metabolic approach to modelling. So far, ASM1 is the most widely applied. Applications of Activated Sludge Models has been prepared in celebration of 25 years of ASM1 and in tribute to the activated sludge modelling pioneer, the late Professor G.v.R. Marrais. It consists of a dozen of practical applications for ASM models to model development, plant optimization, extension, upgrade, retrofit and troubleshooting, carried out by the members of the Delft modelling group over the last two decades.
  data table sensitivity analysis: Energy Management Handbook, Fifth Edition Steve Doty, Wayne C. Turner, 2004-09-22 Originally published two decades ago, the Energy Management Handbook has become recognized as the definitive stand-alone energy manager's desk reference, used by thousands of energy management professionals throughout the industry. Known as the bible of energy management, it has helped more energy managers reach their potential than any other resource. Completely revised and updated, the fifth edition includes new chapters on building commissioning and green buildings. You'll find in-depth coverage of every component of effective energy management, including boiler and steam system optimization, lighting and electrical systems, HVAC system performance, waste heat recovery, cogeneration, thermal energy storage, energy management control systems, energy systems maintenance, building envelope, industrial insulation, indoor air quality, energy economic analysis, energy procurement decision making, energy security and reliability, and overall energy management program organization. You'll also get the latest facts on utility deregulation, energy project financing, and in-house vs. outsourcing of energy services. The energy industry has change radically since the initial publication of this reference over 20 years ago. Looking back on the energy arena, one thing becomes clear: energy is the key element that must be managed to ensure a company's profitability. The Energy Management Handbook, Fifth Edition is the definitive reference to guide energy managers through the maze of changes the industry has experienced.
  data table sensitivity analysis: Financial Modeling Mastery William Johnson, 2024-10-11 Financial Modeling Mastery: Building Robust Models for Market Success is a comprehensive guide crafted to empower readers with the essential skills and knowledge needed to navigate the intricate world of financial modeling. Geared towards both novices and seasoned professionals, this book delves into the foundational principles of quantitative finance, portfolio management, and financial market dynamics, while seamlessly integrating advanced topics such as machine learning, algorithmic trading, and risk management. Through clear explanations and real-world applications, readers will gain the ability to construct sophisticated models that inform strategic decision-making and optimize investment strategies. Each chapter is meticulously designed to build upon the last, ensuring a coherent understanding of how various mathematical tools, valuation techniques, and data analysis methods translate into actionable financial insights. The practical focus is augmented by a deep dive into the ethical considerations and best practices necessary for creating transparent and reliable models. By the conclusion of this volume, readers will not only possess a robust toolkit for financial analysis but also the confidence to leverage these models to identify opportunities and mitigate risks in today's complex financial landscape.
  data table sensitivity analysis: Making the Compelling Business Case W. Messner, 2013-11-26 Providing the necessary background information and hands-on tools to build compelling business cases, this book will increase the reader's capability to champion new business development ideas, take them to senior management, and facilitate the decision process by understanding the key theories and practices of finance and corporate investments.
  data table sensitivity analysis: Microsoft Excel 2019 Data Analysis and Business Modeling Wayne Winston, 2019-03-28 Master business modeling and analysis techniques with Microsoft Excel 2019 and Office 365 and transform data into bottom-line results. Written by award-winning educator Wayne Winston, this hands-on, scenario-focused guide helps you use Excel to ask the right questions and get accurate, actionable answers. New coverage ranges from Power Query/Get & Transform to Office 365 Geography and Stock data types. Practice with more than 800 problems, many based on actual challenges faced by working analysts. Solve real business problems with Excel—and build your competitive advantage: Quickly transition from Excel basics to sophisticated analytics Use PowerQuery or Get & Transform to connect, combine, and refine data sources Leverage Office 365’s new Geography and Stock data types and six new functions Illuminate insights from geographic and temporal data with 3D Maps Summarize data with pivot tables, descriptive statistics, histograms, and Pareto charts Use Excel trend curves, multiple regression, and exponential smoothing Delve into key financial, statistical, and time functions Master all of Excel’s great charts Quickly create forecasts from historical time-based data Use Solver to optimize product mix, logistics, work schedules, and investments—and even rate sports teams Run Monte Carlo simulations on stock prices and bidding models Learn about basic probability and Bayes’ Theorem Use the Data Model and Power Pivot to effectively build and use relational data sources inside an Excel workbook Automate repetitive analytics tasks by using macros
  data table sensitivity analysis: Project Management Ted Klastorin, Gary Mitchell, 2020-08-13 As the number and size of projects continue to increase, there is a growing demand for effective project managers. Project Management: A Risk-Management Approach prepares students to successfully navigate the many challenges, factors, and situations that project managers face. Authors Ted Klastorin and Gary Mitchell emphasize the importance of mitigating risk at every stage, helping students avoid common pitfalls that lead to project failures, compromised schedules, or incurred costs. Real-world examples, cases, solved problems, and practice problems help bring methodologies to life. Readers will be equipped with the tools they need to plan, schedule, and monitor even the most complex projects in a variety of market sectors. Included with this title: The password-protected Instructor Resource Site (formally known as SAGE Edge) offers access to all text-specific resources, including a test bank and editable, chapter-specific PowerPoint® slides.
  data table sensitivity analysis: Engineering Economics for the 21st Century Paul Marnell, 2016-03-21 Provides a modern presentation that eliminates the seven limitations of past and present engineering economics texts: Contains the 12-FACTOR Calculator, an Excel spreadsheet designed by author to provide the values of the 12 factors of engineering economics for arbitrary values of i, g ( ), and N Contains the ANNUAL and PRESENT WORTH COMPARISON Calculators with Component Replacements forcomparing equipment purchase quotations Defines quasi-simple investments and presents a Step-by-Step procedure for calculating their IRRs and balances Presents a classification of the four common non-simple investments and provides Step-by-Step procedures for calculating their IRRs and balances Compares the different profitability measures for the same investment: pretax IRR, aftertax IRR, aftertax sensitivity analysis, net present value, accounting rate of return, benefit-cost ratio, and payback period
  data table sensitivity analysis: Cochrane Handbook for Systematic Reviews of Interventions Julian P. T. Higgins, Sally Green, 2008-11-24 Healthcare providers, consumers, researchers and policy makers are inundated with unmanageable amounts of information, including evidence from healthcare research. It has become impossible for all to have the time and resources to find, appraise and interpret this evidence and incorporate it into healthcare decisions. Cochrane Reviews respond to this challenge by identifying, appraising and synthesizing research-based evidence and presenting it in a standardized format, published in The Cochrane Library (www.thecochranelibrary.com). The Cochrane Handbook for Systematic Reviews of Interventions contains methodological guidance for the preparation and maintenance of Cochrane intervention reviews. Written in a clear and accessible format, it is the essential manual for all those preparing, maintaining and reading Cochrane reviews. Many of the principles and methods described here are appropriate for systematic reviews applied to other types of research and to systematic reviews of interventions undertaken by others. It is hoped therefore that this book will be invaluable to all those who want to understand the role of systematic reviews, critically appraise published reviews or perform reviews themselves.
  data table sensitivity analysis: Financial Modeling Joachim Häcker, Dietmar Ernst, 2017-12-11 This book provides a comprehensive introduction to modern financial modeling using Excel, VBA, standards of financial modeling and model review. It offers guidance on essential modeling concepts around the four core financial activities in the modern financial industry today: financial management; corporate finance; portfolio management and financial derivatives. Written in a highly practical, market focused manner, it gives step-by-step guidance on modeling practical problems in a structured manner. Quick and interactive learning is assured due to the structure as a training course which includes applied examples that are easy to follow. All applied examples contained in the book can be reproduced step by step with the help of the Excel files. The content of this book serves as the foundation for the training course Certified Financial Modeler. In an industry that is becoming increasingly complex, financial modeling is a key skill for practitioners across all key sectors of finance and banking, where complicated problems often need to be solved quickly and clearly. This book will equip readers with the basic modeling skills required across the industry today.
  data table sensitivity analysis: Corporate and Project Finance Modeling Edward Bodmer, 2014-10-10 A clear and comprehensive guide to financial modeling and valuation with extensive case studies and practice exercises Corporate and Project Finance Modeling takes a clear, coherent approach to a complex and technical topic. Written by a globally-recognized financial and economic consultant, this book provides a thorough explanation of financial modeling and analysis while describing the practical application of newly-developed techniques. Theoretical discussion, case studies and step-by-step guides allow readers to master many difficult modeling problems and also explain how to build highly structured models from the ground up. The companion website includes downloadable examples, templates, and hundreds of exercises that allow readers to immediately apply the complex ideas discussed. Financial valuation is an in-depth process, involving both objective and subjective parameters. Precise modeling is critical, and thorough, accurate analysis is what bridges the gap from model to value. This book allows readers to gain a true mastery of the principles underlying financial modeling and valuation by helping them to: Develop flexible and accurate valuation analysis incorporating cash flow waterfalls, depreciation and retirements, updates for new historic periods, and dynamic presentation of scenario and sensitivity analysis; Build customized spreadsheet functions that solve circular logic arising in project and corporate valuation without cumbersome copy and paste macros; Derive accurate measures of normalized cash flow and implied valuation multiples that account for asset life, changing growth, taxes, varying returns and cost of capital; Incorporate stochastic analysis with alternative time series equations and Monte Carlo simulation without add-ins; Understand valuation effects of debt sizing, sculpting, project funding, re-financing, holding periods and credit enhancements. Corporate and Project Finance Modeling provides comprehensive guidance and extensive explanation, making it essential reading for anyone in the field.
  data table sensitivity analysis: Principles of Financial Modelling Michael Rees, 2018-07-10 The comprehensive, broadly-applicable, real-world guide to financial modelling Principles of Financial Modelling – Model Design and Best Practices Using Excel and VBAcovers the full spectrum of financial modelling tools and techniques in order to provide practical skills that are grounded in real-world applications. Based on rigorously-tested materials created for consulting projects and for training courses, this book demonstrates how to plan, design and build financial models that are flexible, robust, transparent, and highly applicable to a wide range of planning, forecasting and decision-support contexts. This book integrates theory and practice to provide a high-value resource for anyone wanting to gain a practical understanding of this complex and nuanced topic. Highlights of its content include extensive coverage of: Model design and best practices, including the optimisation of data structures and layout, maximising transparency, balancing complexity with flexibility, dealing with circularity, model audit and error-checking Sensitivity and scenario analysis, simulation, and optimisation Data manipulation and analysis The use and choice of Excel functions and functionality, including advanced functions and those from all categories, as well as of VBA and its key areas of application within financial modelling The companion website provides approximately 235 Excel files (screen-clips of most of which are shown in the text), which demonstrate key principles in modelling, as well as providing many examples of the use of Excel functions and VBA macros. These facilitate learning and have a strong emphasis on practical solutions and direct real-world application. For practical instruction, robust technique and clear presentation, Principles of Financial Modelling is the premier guide to real-world financial modelling from the ground up. It provides clear instruction applicable across sectors, settings and countries, and is presented in a well-structured and highly-developed format that is accessible to people with different backgrounds.
Data and Digital Outputs Management Plan (DDOMP)
Data and Digital Outputs Management Plan (DDOMP)

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6 Sensitivity Analysis - University of Washington
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