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Statistics, Data Analysis, and Decision Modeling
Author: James R. Evans
Publisher: Prentice Hall
ISBN: 0132744287
Pages: 528
Year: 2013
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A pragmatic approach to statistics, data analysis and decision modeling. Statistics, Data Analysis & Decision Modeling focuses on the practical understanding of its topics, allowing readers to develop conceptual insight on fundamental techniques and theories. Evans' dedication to present material in a simple and straightforward fashion is ideal for comprehension.
Statistics, Data Analysis, and Decision Modeling: International Edition
Author: James R Evans
Publisher: Pearson Higher Ed
ISBN: 027377574X
Pages: 560
Year: 2013-03-20
View: 348
Read: 163
For undergraduate and graduate level courses that combines introductory statistics with data analysis or decision modeling. A pragmatic approach to statistics, data analysis and decision modeling. Statistics, Data Analysis & Decision Modeling focuses on the practical understanding of its topics, allowing readers to develop conceptual insight on fundamental techniques and theories. Evans’ dedication to present material in a simple and straightforward fashion is ideal for student comprehension.
Decision Analytics
Author: Conrad George Carlberg
Publisher: Que Publishing
ISBN: 0789751682
Pages: 272
Year: 2013
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Explains how to distil big data into manageable sets and use them to optimise business and investment decisions. Reveals techniques to improve a wide range of decisions, and use simple Excel charts to grasp the results. Includes downloadable Excel workbooks to adapt to your own requirements.
Microsoft Excel Data Analysis and Business Modeling
Author: Wayne Winston
Publisher: Microsoft Press
ISBN: 1509304223
Pages: 984
Year: 2016-11-29
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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
Regression Analysis
Author: J. Holton Wilson, Barry P. Keating, Mary Beal
Publisher: Business Expert Press
ISBN: 1631573861
Pages: 194
Year: 2015-12-11
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The technique of regression analysis is used so often in business and economics today that an understanding of its use is necessary for almost everyone engaged in the field. This book covers essential elements of building and understanding regression models in a business/economic context in an intuitive manner. The book provides a non-theoretical treatment that is accessible to readers with even a limited statistical background. This book describes exactly how regression models are developed and evaluated. The data used in the book are the kind of data managers are faced with in the real world. The book provides instructions and screen shots for using Microsoft Excel to build business/economic regression models. Upon completion, the reader will be able to interpret the output of the regression models and evaluate the models for accuracy and shortcomings.
Business Analysis
Author: Conrad Carlberg
Publisher: Pearson Education
ISBN: 0789746891
Pages: 528
Year: 2010-06-09
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ANSWER KEY BUSINESS QUESTIONS CONTROL COMPANY FINANCES FORECAST SALES PREPARE BUSINESS CASES MAKE BETTER INVESTMENT DECISIONS IMPROVE QUALITY USE EXCEL 2010 TO GAIN DEEPER INSIGHTS, MAKE SMARTER DECISIONS, AND EARN MORE PROFITS Using real-world examples, Carlberg helps you put Excel’s features and functions to work and get the power of quantitative analysis behind your management decisions. Excel expert Conrad Carlberg shows how to use Excel 2010 to perform the core financial tasks every manager and entrepreneur must master: analyzing statements, planning and controlling company finances, making investment decisions, and managing sales and marketing. Using real-world examples, Carlberg helps you get the absolute most out of Excel 2010’s newest features and functions. Along the way, you’ll discover the fastest, best ways to handle essential tasks ranging from importing business data to analyzing profitability ratios. Becoming an Excel expert has never been easier! You’ll find crystal-clear instructions, insider insights, complete step-by-step projects, and more. It’s all complemented by an extraordinary set of web-based resources, from sample journals and ledgers to business forecasting tools. • Use Excel analysis tools to solve problems throughout the business • Build and work with income statements and balance sheets • Value inventories and current assets, and summarize transactions • Calculate working capital and analyze cash flows • Move from pro formas to operating budgets that help guide your management decisions • Prepare business cases incorporating everything from discount rates to margin and contribution analysis About MrExcel Library: Every book in the MrExcel Library pinpoints a specific set of crucial Excel skills, and presents focused tasks and examples for performing them rapidly and effectively. Selected by Bill Jelen, Microsoft Excel MVP and mastermind behind the leading Excel solutions website MrExcel.com, these books will: • Dramatically increase your productivity–saving you 50 hours a year, or more • Present proven, creative strategies for solving real-world problems • Show you how to get great results, no matter how much data you have • Help you avoid critical mistakes that even experienced users make
The Elements of Statistical Learning
Author: Trevor Hastie, Robert Tibshirani, Jerome Friedman
Publisher: Springer Science & Business Media
ISBN: 0387216065
Pages: 536
Year: 2013-11-11
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During the past decade there has been an explosion in computation and information technology. With it have come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics. Many of these tools have common underpinnings but are often expressed with different terminology. This book describes the important ideas in these areas in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of color graphics. It should be a valuable resource for statisticians and anyone interested in data mining in science or industry. The book’s coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting---the first comprehensive treatment of this topic in any book. This major new edition features many topics not covered in the original, including graphical models, random forests, ensemble methods, least angle regression & path algorithms for the lasso, non-negative matrix factorization, and spectral clustering. There is also a chapter on methods for “wide” data (p bigger than n), including multiple testing and false discovery rates. Trevor Hastie, Robert Tibshirani, and Jerome Friedman are professors of statistics at Stanford University. They are prominent researchers in this area: Hastie and Tibshirani developed generalized additive models and wrote a popular book of that title. Hastie co-developed much of the statistical modeling software and environment in R/S-PLUS and invented principal curves and surfaces. Tibshirani proposed the lasso and is co-author of the very successful An Introduction to the Bootstrap. Friedman is the co-inventor of many data-mining tools including CART, MARS, projection pursuit and gradient boosting.
Predictive Analytics
Author: Conrad Carlberg
Publisher: Que Publishing
ISBN: 013468382X
Pages: 384
Year: 2017-07-24
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EXCEL 2016 PREDICTIVE ANALYTICS FOR SERIOUS DATA CRUNCHERS! Now, you can apply cutting-edge predictive analytics techniques to help your business win–and you don’t need multimillion-dollar software to do it. All the tools you need are available in Microsoft Excel 2016, and all the knowledge and skills are right here, in this book! Microsoft Excel MVP Conrad Carlberg shows you how to use Excel predictive analytics to solve real problems in areas ranging from sales and marketing to operations. Carlberg offers unprecedented insight into building powerful, credible, and reliable forecasts, helping you gain deep insights from Excel that would be difficult to uncover with costly tools such as SAS or SPSS. Fully updated for Excel 2016, this guide contains valuable new coverage of accounting for seasonality and managing complex consumer choice scenarios. Throughout, Carlberg provides downloadable Excel 2016 workbooks you can easily adapt to your own needs, plus VBA code–much of it open-source–to streamline especially complex techniques. Step by step, you’ll build on Excel skills you already have, learning advanced techniques that can help you increase revenue, reduce costs, and improve productivity. By mastering predictive analytics, you’ll gain a powerful competitive advantage for your company and yourself. Learn the “how” and “why” of using data to make better decisions, and choose the right technique for each problem Capture live real-time data from diverse sources, including third-party websites Use logistic regression to predict behaviors such as “will buy” versus “won’t buy” Distinguish random data bounces from real, fundamental changes Forecast time series with smoothing and regression Account for trends and seasonality via Holt-Winters smoothing Prevent trends from running out of control over long time horizons Construct more accurate predictions by using Solver Manage large numbers of variables and unwieldy datasets with principal components analysis and Varimax factor rotation Apply ARIMA (Box-Jenkins) techniques to build better forecasts and clarify their meaning Handle complex consumer choice problems with advanced logistic regression Benchmark Excel results against R results
Simulation Modeling and Analysis
Author: Averill Law
Publisher: McGraw-Hill Higher Education
ISBN: 0077595963
Pages: 804
Year: 2014-01-24
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Since the publication of the first edition in 1982, the goal of Simulation Modeling and Analysis has always been to provide a comprehensive, state-of-the-art, and technically correct treatment of all important aspects of a simulation study. The book strives to make this material understandable by the use of intuition and numerous figures, examples, and problems. It is equally well suited for use in university courses, simulation practice, and self study. The book is widely regarded as the “bible” of simulation and now has more than 100,000 copies in print.
Customer and Business Analytics
Author: Daniel S. Putler, Robert E. Krider
Publisher: CRC Press
ISBN: 149875970X
Pages: 315
Year: 2015-09-15
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Customer and Business Analytics: Applied Data Mining for Business Decision Making Using R explains and demonstrates, via the accompanying open-source software, how advanced analytical tools can address various business problems. It also gives insight into some of the challenges faced when deploying these tools. Extensively classroom-tested, the text is ideal for students in customer and business analytics or applied data mining as well as professionals in small- to medium-sized organizations. The book offers an intuitive understanding of how different analytics algorithms work. Where necessary, the authors explain the underlying mathematics in an accessible manner. Each technique presented includes a detailed tutorial that enables hands-on experience with real data. The authors also discuss issues often encountered in applied data mining projects and present the CRISP-DM process model as a practical framework for organizing these projects. Showing how data mining can improve the performance of organizations, this book and its R-based software provide the skills and tools needed to successfully develop advanced analytics capabilities.
Next Generation Excel
Author: Isaac Gottlieb
Publisher: John Wiley & Sons
ISBN: 1118469089
Pages: 256
Year: 2013-02-04
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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.
The Little SAS Book
Author: Lora D. Delwiche, Susan J. Slaughter
Publisher: SAS Institute
ISBN: 1612904009
Pages: 376
Year: 2012-10-12
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A classic that just keeps getting better, The Little SAS Book is essential for anyone learning SAS programming. Lora Delwiche and Susan Slaughter offer a user-friendly approach so readers can quickly and easily learn the most commonly used features of the SAS language. Each topic is presented in a self-contained two-page layout complete with examples and graphics. The fifth edition has been completely updated to reflect the new default output introduced with SAS 9.3. In addition, there is a now a full chapter devoted to ODS Graphics including the SGPLOT and SGPANEL procedures. Other changes include expanded coverage of linguistic sorting and a new section on concatenating macro variables with other text. This book is a great tool for users of SAS 9.4 as well. This title belongs on every SAS programmer's bookshelf. It's a resource not just to get you started, but one you'll return to as you continue to improve your programming skills. This book is part of the SAS Press program.
Statistical Analysis
Author: Conrad Carlberg
Publisher: Que Publishing
ISBN: 0134840488
Pages: 576
Year: 2017-11-15
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USE EXCEL’S STATISTICAL TOOLS TO TRANSFORM YOUR DATA INTO KNOWLEDGE Nationally recognized Excel expert Conrad Carlberg shows you how to use Excel 2016 to perform core statistical tasks every business professional, student, and researcher should master. Using real-world examples and downloadable workbooks, Carlberg helps you choose the right technique for each problem and get the most out of Excel’s statistical features. Along the way, he clarifies confusing statistical terminology and helps you avoid common mistakes. You’ll learn how to use correlation and regression, analyze variance and covariance, and test statistical hypotheses using the normal, binomial, t, and F distributions. To help you make accurate inferences based on samples from a population, Carlberg offers insightful coverage of crucial topics ranging from experimental design to the statistical power of F tests. Updated for Excel 2016, this guide covers both modern consistency functions and legacy compatibility functions. Becoming an expert with Excel statistics has never been easier! In this book, you’ll find crystal-clear instructions, insider insights, and complete step-by-step guidance. Master Excel’s most useful descriptive and inferential statistical tools Understand how values cluster together or disperse, and how variables move or classify jointly Tell the truth with statistics—and recognize when others don’t Infer a population’s characteristics from a sample’s frequency distribution Explore correlation and regression to learn how variables move in tandem Use Excel consistency functions such as STDEV.S( ) and STDEV.P( ) Test differences between two means using z tests, t tests, and Excel’s Data Analysis Add-in Identify skewed distributions using Excel’s new built-in box-and-whisker plots and histograms Evaluate statistical power and control risk Explore how randomized block and split plot designs alter the derivation of F-ratios Use coded multiple regression analysis to perform ANOVA with unbalanced factorial designs Analyze covariance with ANCOVA, and properly use multiple covariance Take advantage of Recommended PivotTables, Quick Analysis, and other Excel 2016 shortcuts
Model Selection and Inference
Author: Kenneth P. Burnham, David R. Anderson
Publisher: Springer Science & Business Media
ISBN: 1475729170
Pages: 355
Year: 2013-11-11
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Statisticians and applied scientists must often select a model to fit empirical data. This book discusses the philosophy and strategy of selecting such a model using the information theory approach pioneered by Hirotugu Akaike. This approach focuses critical attention on a priori modeling and the selection of a good approximating model that best represents the inference supported by the data. The book includes practical applications in biology and environmental science.
Business Analytics: Data Analysis & Decision Making
Author: S. Christian Albright, Wayne L. Winston
Publisher: Cengage Learning
ISBN: 1337225274
Pages: 984
Year: 2016-03-31
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Master data analysis, modeling, and spreadsheet use with BUSINESS ANALYTICS: DATA ANALYSIS AND DECISION MAKING, 6E! Popular with students, instructors, and practitioners, this quantitative methods text delivers the tools to succeed with its proven teach-by-example approach, user-friendly writing style, and complete Excel 2016 integration. It is also compatible with Excel 2013, 2010, and 2007. Completely rewritten, Chapter 17, Data Mining, and Chapter 18, Importing Data into Excel, include increased emphasis on the tools commonly included under the Business Analytics umbrella -- including Microsoft Excel’s “Power BI” suite. In addition, up-to-date problem sets and cases provide realistic examples to show the relevance of the material. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.