Newly revised to specifically provide demonstration in Excel 2019, this volume shows the capabilities of Microsoft Excel in business statistics. Similar to its predecessor, Excel 2016 for Business Statistics, it is a step-by-step, exercise-driven guide for students and practitioners who are looking to master Excel to solve practical business problems. Excel, a widely available computer program for students and professionals, is also an effective teaching and learning tool for quantitative analyses in business courses. Its powerful computational ability and graphical functions make learning statistics much easier than in years past. Excel 2019 for Business Statistics: A Guide to Solving Practical Problems capitalizes on these improvements by teaching students and managers 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 business 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 offers a wealth of new sample problems, as well as updated chapter content throughout.

The revised Fifth Edition of this popular textbook is redesigned with Excel 2019 and the new inclusion of interactive, user-friendly JMP to encourage business students to develop competitive advantages for use in their future careers. Students learn to build models, produce statistics, and translate results into implications for decision makers. The text features new and updated examples and assignments, and each chapter discusses a focal case from the business world which can be analyzed using the statistical strategies and software provided in the text. Paralleling recent interest in climate change and sustainability, new case studies concentrate on issues such as the impact of drought on business, automobile emissions, and sustainable package goods. The book continues its coverage of inference, Monte Carlo simulation, contingency analysis, and linear and nonlinear regression. A new chapter is dedicated to conjoint analysis design and analysis, including complementary use of regression and JMP.​ For access to accompanying data sets, please email author Cynthia Fraser at cfg8q@virginia.edu.

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.

Newly revised for Excel 2019, this text is a step-by-step guide for students taking a first course in statistics for advertising and for advertising managers and practitioners who want to learn how to use Excel to solve practical statistics problems in the workplace, whether or not they have taken a course in statistics. Excel 2019 for Advertising Statistics explains statistical formulas and offers practical examples for how students can solve real-world advertising statistics problems. Each chapter offers a concise overview of a topic, and then demonstrates how to use Excel commands and formulas to solve specific advertising statistics problems. This book demonstrates how to use Excel 2019 in two different ways: (1) writing formulas (e.g., confidence interval about the mean, one-group t-test, two-group t-test, correlation) and (2) using Excel’s drop-down formula menus (e.g., simple linear regression, multiple correlation and multiple regression, and one-way ANOVA). Three practice problems are provided at the end of each chapter, along with their solutions in an appendix. An additional practice test allows readers to test their understanding of each chapter by attempting to solve a specific practical advertising statistics problem using Excel; the solution to each of these problems is also given in an appendix. This latest edition features a wealth of new end-of-chapter problems and an update of the chapter content throughout. ​

This book shows the capabilities of Microsoft Excel in teaching social science statistics effectively. Similar to the previously published Excel 2016 for Social Sciences Statistics, this book is a step-by-step, exercise-driven guide for students and practitioners who need to master Excel to solve practical social science problems. If understanding statistics isn’t your strongest suit, you are not especially mathematically inclined, or 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 social science courses. Its powerful computational ability and graphical functions make learning statistics much easier than in years past. Excel 2019 for Social Science Statistics: A Guide to Solving Practical Problems capitalizes on these improvements by teaching students and managers how to apply Excel to statistical techniques necessary in their courses and work. In this new edition, each chapter explains statistical formulas and directs the reader to use Excel commands to solve specific, easy-to-understand social science 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 book shows the capabilities of Microsoft Excel in teaching human resource management statistics effectively. Similar to the previously published Excel 2016 for Human Resource Management Statistics, this book is a step-by-step, exercise-driven guide for students and practitioners who need to master Excel to solve practical human resource management problems. 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 human resource management courses. Its powerful computational ability and graphical functions make learning statistics much easier than in years past. However, Excel 2019 for Human Resource Management Statistics: A Guide to Solving Practical Problems, 2nd Edition, capitalizes on these improvements by teaching students and managers 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 human resource management 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.

Newly revised to specifically address Microsoft Excel 2019, this book shows the capabilities of Excel in teaching educational and psychological statistics effectively. Similar to the previously published Excel 2016 for Educational and Psychological Statistics, it is a step-by-step, exercise-driven guide for students and practitioners who need to master Excel to solve practical education and psychology problems. Excel, a widely available computer program for students and managers, is also an effective teaching and learning tool for quantitative analyses in education and psychology courses. Its powerful computational ability and graphical functions make learning statistics much easier than in years past. Excel 2019 for Educational and Psychological Statistics capitalizes on these improvements by teaching students and managers 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 educational and psychological 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 chapter problems and solutions, as well as updated chapter content throughout.

Newly revised to specifically address Microsoft Excel 2019, this book is a step-by-step, exercise-driven guide for students and practitioners who need to master Excel to solve practical biological and life science problems. Excel is an effective learning tool for quantitative analyses in biological and life sciences courses. Its powerful computational ability and graphical functions make learning statistics much easier than in years past. Excel 2019 for Biological and Life Sciences Statistics capitalizes on these improvements by teaching students and professionals how to apply Excel 2019 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 biological and life science 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 offers a wealth of new practice problems and solutions, as well as updated chapter content throughout.

This book gives readers a hands-on understanding of Excel-assisted statistical techniques to take effective business decisions. It showcases applications of the tools and techniques of statistics for analysing business data from the domain of business statistics. The volume provides an exhaustive introduction to the application of statistics in solving business problems and implementing data analytics for effective decision making in all kinds of business situations around the world. With an emphasis on simplicity in presentation of concepts of statistical methods and associated Excel functions, the volume explores the implementation of Excel functions through well-defined sequences of steps. It covers an array of key topics which include Discussions on real-world problems, decision support systems, scope of business statistics, types, and steps of research; Introduction to Excel and its mathematical and preliminary statistical functions; usage of different types of average functions; mean, median, and mode functions; measures of variation; measures of skewness of Excel; In-depth discussions on probability distributions, sampling distributions, testing of hypothesis, chi-square test, non-parametric tests of Excel; Extensive coverage on correlation and covariance, forecasting, analysis of variance, charts in Excel; and Analysis of the concept of linear programming, problem formulations, and techniques of linear programming, followed by the application in Excel. Comprehensive in scope and simple in approach, this book will be key for students and researchers of business studies, business administration, economics, finance, commerce, data analytics/science, and computer science. This will also serve as useful guidebook for business executives and working professionals across the globe.

This text is a step-by-step, exercise-driven guide for students and practitioners who need to master Excel to solve practical social work problems. 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 social work courses. Its powerful computational ability and graphical functions make learning statistics much easier than in years past. Excel 2019 for Social Work Statistics: A Guide to Solving Practical Problems capitalizes on these improvements by teaching students and managers how to apply Excel to statistical techniques necessary in their courses and work. In this new edition, each chapter explains statistical formulas and directs the reader to use Excel commands to solve specific, easy-to-understand social work 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.