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24 result(s) for "Industrial management Statistical methods Computer programs."
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Excel Data Analysis
Professional-level coverage and techniques for Excel power users Aimed at Excel power users who appreciate logical, clean explanations of techniques, this visual guide features numerous screenshots and easy-to-follow numbered steps in order to show you how to perform professional-level modeling, charting, data sharing, data access, data slicing, and other functions. You'll find super techniques for getting the most out of Excel's statistical and financial functions, Excel PivotTables and PivotCharts, Excel Solver, and more. Demonstrates how to crunch and analyze Excel data the way the professionals do in an uncluttered, visual style Offers a clear look at power-using the new Excel 2013, the latest version of the world's leading spreadsheet application from Microsoft Expands your Excel knowledge and helps you use Excel data more efficiently Explains how to retrieve data from databases; cut, slice, and pivot data using PivotTables; model data and chart data; and use advanced formulas Explores all features and functions in two-color pages packed with screenshots, numbered steps, and other visual graphics that clearly show you how to accomplish tasks Includes practical examples, tips, and advice to help you get the most out of Excel's features and functions Learn the full power of Excel 2013 with this helpful guide!.
Excel Data Analysis
Professional-level coverage and techniques for Excel power users Aimed at Excel power users who appreciate logical, clean explanations of techniques, this visual guide features numerous screenshots and easy-to-follow numbered steps in order to show you how to perform professional-level modeling, charting, data sharing, data access, data slicing, and other functions. You'll find super techniques for getting the most out of Excel's statistical and financial functions, Excel PivotTables and PivotCharts, Excel Solver, and more. Demonstrates how to crunch and analyze Excel data the way the professionals do in an uncluttered, visual style Offers a clear look at power-using the new Excel 2013, the latest version of the world's leading spreadsheet application from Microsoft Expands your Excel knowledge and helps you use Excel data more efficiently Explains how to retrieve data from databases; cut, slice, and pivot data using PivotTables; model data and chart data; and use advanced formulas Explores all features and functions in two-color pages packed with screenshots, numbered steps, and other visual graphics that clearly show you how to accomplish tasks Includes practical examples, tips, and advice to help you get the most out of Excel's features and functions Learn the full power of Excel 2013 with this helpful guide!.
Storytelling with data
Don't simply show your data—tell a story with it!Storytelling with Data teaches you the fundamentals of data visualization and how to communicate effectively with data. You'll discover the power of storytelling and the way to make data a pivotal point in your story. The lessons in this illuminative text are grounded in theory, but made accessible through numerous real-world examples—ready for immediate application to your next graph or presentation.Storytelling is not an inherent skill, especially when it comes to data visualization, and the tools at our disposal don't make it any easier. This book demonstrates how to go beyond conventional tools to reach the root of your data, and how to use your data to create an engaging, informative, compelling story. Specifically, you'll learn how to:Understand the importance of context and audienceDetermine the appropriate type of graph for your situationRecognize and eliminate the clutter clouding your informationDirect your audience's attention to the most important parts of your dataThink like a designer and utilize concepts of design in data visualizationLeverage the power of storytelling to help your message resonate with your audienceTogether, the lessons in this book will help you turn your data into high impact visual stories that stick with your audience. Rid your world of ineffective graphs, one exploding 3D pie chart at a time. There is a story in your data—Storytelling with Data will give you the skills and power to tell it!
Computational Methods for Measuring the Difference of Empirical Distributions
This paper presents a simple computational method for measuring the difference of independent empirical distributions estimated by bootstrapping or other resampling approaches. Using data from a field test of external scope in contingent valuation, this complete combinatorial method is compared with other methods (empirical convolutions, repeated sampling, normality, nonoverlapping confidence intervals) that have been suggested in the literature. Tradeoffs between methods are discussed in terms of programming complexity, time and computer resources required, bias, and the precision of the estimate.
Assessment and modeling of the groundwater hydrogeochemical quality parameters via geostatistical approaches
Geostatistical methods are one of the advanced techniques used for interpolation of groundwater quality data. The results obtained from geostatistics will be useful for decision makers to adopt suitable remedial measures to protect the quality of groundwater sources. Data used in this study were collected from 78 wells in Varamin plain aquifer located in southeast of Tehran, Iran, in 2013. Ordinary kriging method was used in this study to evaluate groundwater quality parameters. According to what has been mentioned in this paper, seven main quality parameters (i.e. total dissolved solids (TDS), sodium adsorption ratio (SAR), electrical conductivity (EC), sodium (Na+), total hardness (TH), chloride (Cl−) and sulfate (SO42−)), have been analyzed and interpreted by statistical and geostatistical methods. After data normalization by Nscore method in WinGslib software, variography as a geostatistical tool to define spatial regression was compiled and experimental variograms were plotted by GS+ software. Then, the best theoretical model was fitted to each variogram based on the minimum RSS. Cross validation method was used to determine the accuracy of the estimated data. Eventually, estimation maps of groundwater quality were prepared in WinGslib software and estimation variance map and estimation error map were presented to evaluate the quality of estimation in each estimated point. Results showed that kriging method is more accurate than the traditional interpolation methods.
Excel dashboards & reports for dummies
Create dynamic dashboards and put your data on display with For Dummies No matter what business you're in, reports have become a staple of the workplace, but what good is a report if no reads it, or even worse, understands it? This all new edition of Excel Dashboards & Reports For Dummies is here to help you make meaning of all your data and turn it into clear and actionable visualizations. Fully updated for the latest business intelligence and spreadsheet tools in Excel 2013, this book shows you how to analyze large amounts of data, quickly slice data into various views on the fly, automate redundant reporting, create eye-catching visualizations, and more. Helps you move beyond reporting data with simple tables, rows, and columns to designing high-impact reports, dashboards, and visuals Walks you through a wide array of technical and analytical concepts to give you the background you need to select the right tool for interpreting and displaying data Covers how to build a chart, work with pivot tables, group and bucket your data, represent trends, create What-If analyses, and increase the value of your reports Excel Dashboards & Reports For Dummies, 2nd Edition is the business analysis tool you need to transform your raw data into a powerful and effective presentation that is accessible to everyone.
Profit-driven business analytics : a practitioner's guide to transforming big data into added value
Maximize profit and optimize decisions with advanced business analytics Profit-Driven Business Analytics provides actionable guidance on optimizing the use of data to add value and drive better business. Combining theoretical and technical insights into daily operations and long-term strategy, this book acts as a development manual for practitioners seeking to conceive, develop, and manage advanced analytical models. Detailed discussion delves into the wide range of analytical approaches and modeling techniques that can help maximize business payoff, and the author team draws upon their recent research to share deep insight about optimal strategy. Real-life case studies and examples illustrate these techniques at work, and provide clear guidance for implementation in your own organization. From step-by-step instruction on data handling, to analytical fine-tuning, to evaluating results, this guide provides invaluable guidance for practitioners seeking to reap the advantages of true business analytics. Despite widespread discussion surrounding the value of data in decision making, few businesses have adopted advanced analytic techniques in any meaningful way. This book shows you how to delve deeper into the data and discover what it can do for your business. * Reinforce basic analytics to maximize profits * Adopt the tools and techniques of successful integration * Implement more advanced analytics with a value-centric approach * Fine-tune analytical information to optimize business decisions Both data stored and streamed has been increasing at an exponential rate, and failing to use it to the fullest advantage equates to leaving money on the table. From bolstering current efforts to implementing a full-scale analytics initiative, the vast majority of businesses will see greater profit by applying advanced methods. Profit-Driven Business Analytics provides a practical guidebook and reference for adopting real business analytics techniques.
Using Excel for Business Analysis
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.
ARL Numerics for MEWMA Charts
The FORTRAN code in Bodden and Rigdon (1999) for the in-control average run length (ARL) of multivariate exponentially weighted moving average charts (MEWMA) became quite popular and is widely used in statistical software systems such as MINITAB and STATISTICA. We find that the algorithms' accuracy is poor for low-dimensional processes. The Markov chain approximation described in Runger and Prabhu (1996) is not able to resolve the issue. The same holds for the calculation of the out-of-control ARL as proposed in Ridgon (1995b). We present two concepts that achieve higher accuracy for all dimensions. The competing numerical procedures are implemented in the R package spc.