This is today’s most complete guide to regression analysis with Microsoft® Excel for any business analytics or research task. Drawing on 25 years of advanced statistical experience, Microsoft MVP Conrad Carlberg shows how to use Excel’s regression-related worksheet functions to perform a wide spectrum of practical analyses. Carlberg clearly explains all the theory you’ll need to avoid mistakes, understand what your regressions are really doing, and evaluate analyses performed by others. From simple correlations and t-tests through multiple analysis of covariance, Carlberg offers hands-on, step-by-step walkthroughs using meaningful examples. He discusses the consequences of using each option and argument, points out idiosyncrasies and controversies associated with Excel’s regression functions, and shows how to use them reliably in fields ranging from medical research to financial analysis to operations. You don’t need expensive software or a doctorate in statistics to work with regression analyses. Microsoft Excel has all the tools you need—and this book has all the knowledge! Understand what regression analysis can and can’t do, and why Master regression-based functions built into all recent versions of Excel Work with correlation and simple regression Make the most of Excel’s improved LINEST() function Plan and perform multiple regression Distinguish the assumptions that matter from the ones that don’t Extend your analysis options by using regression instead of traditional analysis of variance Add covariates to your analysis to reduce bias and increase statistical power
Statistiken und Aussagen zu Wahrscheinlichkeiten begegnen uns heute ï¿1⁄2berall: Die Umsatzentwicklung in Unternehmen, Hochrechnungen fï¿1⁄2r Wahlergebnisse, PISA-Ergebnisse fï¿1⁄2nfzehnjï¿1⁄2hriger Schï¿1⁄2ler sind nur drei von zahlreichen Beispielen. Joseph Schmuller zeigt Ihnen in diesem Buch, wie Sie die Zahlen in den Griff bekommen und Daten, Statistiken und Wahrscheinlichkeiten richtig lesen und interpretieren. Dafï¿1⁄2r brauchen Sie keinen Statistikkurs zu belegen und kein Mathegenie zu sein. Fï¿1⁄2r alles gibt es in Excel die passende Funktion und das passende Werkzeug. So kï¿1⁄2nnen Sie Theorie und Praxis sofort miteinander verbinden.
Use Excel 2013’s statistical tools to transform your data into knowledge Conrad Carlberg shows how to use Excel 2013 to perform core statistical tasks every business professional, student, and researcher should master. Using real-world examples, Carlberg helps you choose the right technique for each problem and get the most out of Excel’s statistical features, including recently introduced consistency functions. 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, this edition adds two more chapters on inferential statistics, covering crucial topics ranging from experimental design to the statistical power of F tests. Becoming an expert with Excel statistics has never been easier! You’ll find crystal-clear instructions, insider insights, and complete step-by-step projects—all complemented by extensive web-based resources. Master Excel’s most useful descriptive and inferential statistical tools Tell the truth with statistics—and recognize when others don’t Accurately summarize sets of values 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 Use ANOVA to test differences between more than two means Explore statistical power by manipulating mean differences, standard errors, directionality, and alpha Take advantage of Recommended PivotTables, Quick Analysis, and other Excel 2013 shortcuts
An applied and concise treatment of statistical regression techniques for business students and professionals who have little or no background in calculus Regression analysis is an invaluable statistical methodology in business settings and is vital to model the relationship between a response variable and one or more predictor variables, as well as the prediction of a response value given values of the predictors. In view of the inherent uncertainty of business processes, such as the volatility of consumer spending and the presence of market uncertainty, business professionals use regression analysis to make informed decisions. Applied Regression Modeling: A Business Approach offers a practical, workable introduction to regression analysis for upper-level undergraduate business students, MBA students, and business managers, including auditors, financial analysts, retailers, economists, production managers, and professionals in manufacturing firms. The book's overall approach is strongly based on an abundant use of illustrations and graphics and uses major statistical software packages, including SPSS(r), Minitab(r), SAS(r), and R/S-PLUS(r). Detailed instructions for use of these packages, as well as for Microsoft Office Excel(r), are provided, although Excel does not have a built-in capability to carry out all the techniques discussed. Applied Regression Modeling: A Business Approach offers special user features, including: * A companion Web site with all the datasets used in the book, classroom presentation slides for instructors, additional problems and ideas for organizing class time around the material in the book, and supplementary instructions for popular statistical software packages. An Instructor's Solutions Manual is also available. * A generous selection of problems-many requiring computer work-in each chapter with fullyworked-out solutions * Two real-life dataset applications used repeatedly in examples throughout the book to familiarize the reader with these applications and the techniques they illustrate * A chapter containing two extended case studies to show the direct applicability of the material * A chapter on modeling extensions illustrating more advanced regression techniques through the use of real-life examples and covering topics not normally seen in a textbook of this nature * More than 100 figures to aid understanding of the material Applied Regression Modeling: A Business Approach fully prepares professionals and students to apply statistical methods in their decision-making, using primarily regression analysis and modeling. To help readers understand, analyze, and interpret business data and make informed decisions in uncertain settings, many of the examples and problems use real-life data with a business focus, such as production costs, sales figures, stock prices, economic indicators, and salaries. A calculus background is not required to understand and apply the methods in the book.
Excel predictive analytics for serious data crunchers! The movie Moneyball made predictive analytics famous: Now you can apply the same techniques to help your business win. You don’t need multimillion-dollar software: All the tools you need are available in Microsoft Excel, 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-world problems in areas ranging from sales and marketing to operations. Carlberg offers unprecedented insight into building powerful, credible, and reliable forecasts, showing how to gain deep insights from Excel that would be difficult to uncover with costly tools such as SAS or SPSS. You’ll get an extensive collection of downloadable Excel workbooks you can easily adapt to your own unique requirements, plus VBA code—much of it open-source—to streamline several of this book’s most 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 both the “how” and “why” of using data to make better tactical decisions • Choose the right analytics technique for each problem • Use Excel to 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 • Construct more accurate predictions by using Solver to find maximum likelihood estimates • Manage huge numbers of variables and enormous datasets with principal components analysis and Varimax factor rotation • Apply ARIMA (Box-Jenkins) techniques to build better forecasts and understand their meaning
A unique, self-study reference for managers and statisticians who use the Excel Spreadsheet as their primary computational tool for forecasting, data analysis, or regression analysis. Original. (Advanced).
Business & Economics by S. Albright,Wayne Winston,Christopher Zappe
Author: S. Albright,Wayne Winston,Christopher Zappe
Publisher: Cengage Learning
Category: Business & Economics
DATA ANALYSIS AND DECISION MAKING emphasizes data analysis, modeling, and spreadsheet use in statistics and management science. This text became a market leader in its first edition for its clarity of writing and teach-by-example approach, and it continues that tradition in this edition. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.
This title has been written as a basic statistical applications book for non-statistics majors. It focuses on the use of Microsoft Excel Add-Ins function in analyzing basic statistical problems. It is intended for beginners, and it introduces statistical concepts in ways that may be relevant to practitioners. The data used throughout the book is based on responses to common social issues. This way, the book can be relevant to multiple users with different backgrounds. The topics covered include: questionnaire design, descriptive statistics; hypothesis testing; confidence interval estimation; nonparametric statistics; and simple and multiple regression analysis. of statistics. Students majoring in business, health sciences, and social sciences are also likely to find the book useful in understanding statistical concepts. Practitioners who may be interested in exploring the power of Microsoft Excel for statistical analysis should also find the book very useful.
Get more out of Microsoft Excel® 2013: more productivity and better answers for greater success! Drawing on his unsurpassed Excel experience, Bill Jelen (“Mr Excel”) brings together all the intensely useful knowledge you need: insights, techniques, tips, and shortcuts you just won’t find anywhere else. Excel 2013 In Depth is the fastest, best way to master Excel 2013’s full power; get comfortable with its updated interface; and leverage its new tools for everything from formulas, charts, and functions to dashboards, data visualization, and social media integration. Start by taking a quick “tour” of Excel 2013’s most valuable new features. Then, learn how to Build more trustworthy, error-resistant, flexible, extensible, intelligent, and understandable spreadsheets Get more productive with Excel 2013’s new Start Screen and Timelines Create formulas, charts, subtotals, and pivot tables faster with new Flash Fill and Analysis Lens Quickly apply attractive, consistent formats Master every function you’ll ever need,- including powerful new web services functions Solve real-world business intelligence analysis problems Create amazing PowerPivot data mashups that integrate information from anywhere Use Power View to generate stunningly intuitive maps, dashboards, and data visualizations Share workbooks on the Web and social networks Leverage the improved Excel Web App to create highly interactive web pages and online surveys Automate repetitive functions using Excel macros Supercharge your workbooks with new apps from the Excel App Store Like all In Depth books, Excel 2013 In Depth delivers complete coverage with detailed solutions, and troubleshooting help for tough problems you can’t fix on your own. Whatever you intend to do with Excel 2013, this is the only book you’ll need!
The personal computer has made statistical analysis easier and cheaper. Previously, statistical analysis was difficult for many reasons. Two of the reasons were: (1) statistical analysis was slow and tedious because calculations were done by hand; (2) it was costly because it was done on mainframes and mainframe time was expensive. This book discusses statistical analysis using two personal computer software packages, Minitab 12 and Microsoft Excel 97, Minitab was chosen because it is powerful and is one of the more user-friendly statistical software packages. Microsoft Excel 97 was selected because it is one of the most important software packages to learn and most companies use Microsoft Excel. Excel is a software package that is not dedicated to statistical analysis like Minitab, but it has many statistical features and a very powerful development environment for writing customized statistical analysis. The book is organized in a textbook format. Each chapter discusses statistical conceptsand illustrates the use of Minitab and/or Excel. Often it becomes necessary to write macros (programs) in order to do specific statistical analysis. This books prints the codes of the macros for the reader to use and study. This is valuable because usually the difficult part is how to write the code. What the reader will find after studying this book is that statistical analysis will become more fun because he will have more time doing statistical analysis and make less statistical calculations.
Business & Economics by Timothy R. Mayes,Todd M. Shank
Taking your spreadsheet skills to the next level, Mayes/Shank's FINANCIAL ANALYSIS WITH MICROSOFT EXCEL 2016, 8E, equips you with a solid foundation in corporate finance while helping you master the tools professionals use every day. It delivers thorough coverage of financial statements, cash budgets, time series forecasting, the Security Market Security Line, pro forma financial statements, cost of capital, VBA programming, Pivot Tables, and Get & Transform tools (formerly known as Power Query). With its unique self-directed learning approach, this reader-friendly book is an ideal resource for independent learning and a valuable reference tool. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.
Business & Economics by J. Holton Wilson,Barry P. Keating,Mary Beal
Understanding and Building Business and Economic Models Using Excel, Second Edition
Author: J. Holton Wilson,Barry P. Keating,Mary Beal
Publisher: Business Expert Press
Category: Business & Economics
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.
This popular best-selling book shows students and professionals how to do data analysis with Microsoft Excel. DATA ANALYSIS WITH MICROSOFT EXCEL teaches the fundamental concepts of statistics and how to use Microsoft Excel to solve the kind of data-intensive problems that arise in business and elsewhere. Even students with no previous experience using spreadsheets will find that this text's step-by-step approach, extensive tutorials, and real-world examples make it easy to learn how to use Excel for analyzing data. A downloadable StatPlus add-in for Microsoft Excel, data sets for exercises, and interactive concept tutorials are available on the Book Companion Website. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.
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
Microsoft Excel can perform many statistical analyses, but thousands of business users and analysts are now reaching its limits. R, in contrast, can perform virtually any imaginable analysis--if you can get over its learning curve. In R for Microsoft� Excel Users, Conrad Carlberg shows exactly how to get the most from both programs. Drawing on his immense experience helping organizations apply statistical methods, Carlberg reviews how to perform key tasks in Excel, and then guides you through reaching the same outcome in R--including which packages to install and how to access them. Carlberg offers expert advice on when and how to use Excel, when and how to use R instead, and the strengths and weaknesses of each tool. Writing in clear, understandable English, Carlberg combines essential statistical theory with hands-on examples reflecting real-world challenges. By the time you've finished, you'll be comfortable using R to solve a wide spectrum of problems--including many you just couldn't handle with Excel. * Smoothly transition to R and its radically different user interface * Leverage the R community's immense library of packages * Efficiently move data between Excel and R * Use R's DescTools for descriptive statistics, including bivariate analyses * Perform regression analysis and statistical inference in R and Excel * Analyze variance and covariance, including single-factor and factorial ANOVA * Use R's mlogit package and glm function for Solver-style logistic regression * Analyze time series and principal components with R and Excel
For Microsoft Excel for Windows 95, and for Microsoft Excel for Windows 3.1 and Macintosh systems, this book provides complete information about each of the more than 300 worksheet functions built into Microsoft Excel for Windows 95. It is a handy way to gain access to one of Excel's most powerful features--those that turn Excel from a mere calculation into a powerful tool.