Newly revised to specifically address Microsoft Excel 2019, this book shows the capabilities of Excel in teaching engineering statistics effectively. Similar to the previously published Excel 2016 for Engineering Statistics, this volume is a step-by-step, exercise-driven guide for students and practitioners who need to master Excel to solve practical engineering problems. Excel, a widely available computer program for students and professionals, is also an effective teaching and learning tool for quantitative analyses in engineering courses. Its powerful computational ability and graphical functions make learning statistics much easier than in years past. Excel 2019 for Engineering Statistics capitalizes on these improvements by teaching readers how to apply Excel to statistical techniques necessary in their courses and work. Each chapter explains statistical formulas and directs the reader to use Excel commands to solve specific, easy-to-understand engineering problems. Practice problems are provided at the end of each chapter with their solutions in an appendix. Separately, there is a full practice test (with answers in an appendix) that allows readers to test what they have learned. This new edition features a wealth of new sample problems and solutions, as well as updated chapter content throughout.

The revised Fourth Edition of this popular textbook is redesigned with Excel 2016 to encourage business students to develop competitive advantages for use in their future careers as decision makers. Students learn to build models using logic and experience, produce statistics using Excel 2016 with shortcuts, and translate results into implications for decision makers. The textbook features new examples and assignments on global markets, including cases featuring Chipotle and Costco. A number of examples focus on business in emerging global markets with particular emphasis on emerging markets in Latin America, China, and India. Results are linked to implications for decision making with sensitivity analyses to illustrate how alternate scenarios can be compared. The author emphasises communicating results effectively in plain English and with screenshots and compelling graphics in the form of memos and PowerPoints. Chapters include screenshots to make it easy to conduct analyses in Excel 2016. PivotTables and PivotCharts, used frequently in business, are introduced from the start. The Fourth Edition features Monte Carlo simulation in four chapters, as a tool to illustrate the range of possible outcomes from decision makers’ assumptions and underlying uncertainties. Model building with regression is presented as a process, adding levels of sophistication, with chapters on multicollinearity and remedies, forecasting and model validation, auto-correlation and remedies, indicator variables to represent segment differences, and seasonality, structural shifts or shocks in time series models. Special applications in market segmentation and portfolio analysis are offered, and an introduction to conjoint analysis is included. Nonlinear models are motivated with arguments of diminishing or increasing marginal response.

Takes the challenging and makes it understandable. The book contains useful advice on the application of statistics to a variety of contexts and shows how statistics can be used by managers in their work.′ - Dr Terri Byers, Assistant Professor, University Of New Brunswick, Canada A book about introductory quantitative analysis, the authors show both how and why quantitative analysis is useful in the context of business and management studies, encouraging readers to not only memorise the content but to apply learning to typical problems. Fully up-to-date with comprehensive coverage of IBM SPSS and Microsoft Excel software, the tailored examples illustrate how the programmes can be used, and include step-by-step figures and tables throughout. A range of ‘real world’ and fictional examples, including "The Ballad of Eddie the Easily Distracted" and "Esha′s Story" help bring the study of statistics alive. A number of in-text boxouts can be found throughout the book aimed at readers at varying levels of study and understanding Back to Basics for those struggling to understand, explain concepts in the most basic way possible - often relating to interesting or humorous examples Above and Beyond for those racing ahead and who want to be introduced to more interesting or advanced concepts that are a little bit outside of what they may need to know Think it over get students to stop, engage and reflect upon the different connections between topics A range of online resources including a set of data files and templates for the reader following in-text examples, downloadable worksheets and instructor materials, answers to in-text exercises and video content compliment the book. An ideal resource for undergraduates taking introductory statistics for business, or for anyone daunted by the prospect of tackling quantitative analysis for the first time.

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

Applied Business Statistics for Business and Management using Microsoft Excel is the first book to illustrate the capabilities of Microsoft Excel to teach applied statistics effectively. It is a step-by-step exercise-driven guide for students and practitioners who need to master Excel to solve practical statistical problems in industry. If understanding statistics isn’t your strongest suit, you are not especially mathematically-inclined, or if you are wary of computers, this is the right book for you. Excel, a widely available computer program for students and managers, is also an effective teaching and learning tool for quantitative analyses in statistics courses. Its powerful computational ability and graphical functions make learning statistics much easier than in years past. However, Applied Business Statistics for Business and Management capitalizes on these improvements by teaching students and practitioners how to apply Excel to statistical techniques necessary in their courses and workplace. Each chapter explains statistical formulas and directs the reader to use Excel commands to solve specific, easy-to-understand business problems. Practice problems are provided at the end of each chapter with their solutions.

Using a familiar tool, such as Excel, enhances the business professionals ability to make better business decisions leading to future success. This manual provides step-by-step instructions for using Excel to solve most of the problems for business statistics. It presents many visual examples of computer screen captures. These show data input, pull-down menus, dialog boxes and statistical results.

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