This is the first book to show the capabilities of Microsoft Excel to teach physical sciences statistics effectively. It is a step-by-step exercise-driven guide for students and practitioners who need to master Excel to solve practical science 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 science courses. Its powerful computational ability and graphical functions make learning statistics much easier than in years past. However, Excel 2010 for Physical Sciences Statistics: A Guide to Solving Practical Problems is the first book to capitalize 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 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. Includes 159 illustrations in color Suitable for undergraduates or graduate students

This book shows the is a step-by-step exercise-driven guide for students and practitioners who need to master Excel to solve practical science 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 science courses. Its powerful computational ability and graphical functions make learning statistics much easier than in years past. However, Excel 2013 for Physical Sciences Statistics: A Guide to Solving Practical Problems is the first book to capitalize 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 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.

"The ability to summarise data, compare models and apply computer-based analysis tools are vital skills necessary for studying and working in the physical sciences. This textbook supports undergraduate students as they develop and enhance these skills. Introducing data analysis techniques, this textbook pays particular attention to the internationally recognised guidelines for calculating and expressing measurement uncertainty. This new edition has been revised to incorporate Excel® 2010. It also provides a practical approach to fitting models to data using non-linear least squares, a powerful technique which can be applied to many types of model. Worked examples using actual experimental data help students understand how the calculations apply to real situations. Over 200 in-text exercises and end-of-chapter problems give students the opportunity to use the techniques themselves and gain confidence in applying them. Answers to the exercises and problems are given at the end of the book"--Provided by publisher.

This book shows the capabilities of Microsoft Excel in teaching physical science statistics effectively. Similar to the previously published Excel 2013 for Physical Sciences Statistics, this book is a step-by-step exercise-driven guide for students and practitioners who need to master Excel to solve practical physical science problems. If understanding statistics isn’t the reader’s strongest suit, the reader is not mathematically inclined, or if the reader is new to computers or to Excel, this is the book to start off with. Excel, a widely available computer program for students and managers, is also an effective teaching and learning tool for quantitative analyses in physical science courses. Its powerful computational ability and graphical functions make learning statistics much easier than in years past. However, Excel 2016 for Physical Sciences 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 physical 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 physical science statistics effectively. Similar to the previously published Excel 2016 for Physical Sciences Statistics, this book is a step-by-step, exercise-driven guide for students and practitioners who need to master Excel to solve practical physical science problems. If understanding statistics isn’t the reader’s strongest suit, the reader is not mathematically inclined, or if the reader is new to computers or to Excel, this is the book to start off with. Excel, a widely available computer program for students and managers, is also an effective teaching and learning tool for quantitative analyses in physical science courses. Its powerful computational ability and graphical functions make learning statistics much easier than in years past. Excel 2019 for Physical Sciences 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 physical 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 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 in the workplace, whether or not they have taken a course in statistics. Excel 2016 for Advertising Statistics explains statistical formulas and offers practical examples for how students can solve real-world advertising statistics problems. This book leaves detailed explanations of statistical theory to other statistics textbooks and focuses entirely on practical, real-world problem solving. Each chapter briefly explains a topic and then demonstrates how to use Excel commands and formulas to solve specific advertising statistics problems. This book gives practice in using Excel 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. · Includes 167 illustrations in color · Suitable for undergraduates or graduate students

This book shows the capabilities of Microsoft Excel in teaching social science statistics effectively. Similar to the previously published Excel 2013 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 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 science courses. Its powerful computational ability and graphical functions make learning statistics much easier than in years past. However, Excel 2016 for Social Science Statistics: A Guide to Solving Practical Problems is the first book to capitalize 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 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. Includes 167 illustrations in color Suitable for upper undergraduates or graduate students At the beginning of his academic career, Prof. Tom J. Quirk spent six years in educational research at The American Institutes for Research and Educational Testing Service. He then taught Social Psychology, Educational Psychology, General Psychology, Marketing, Management, and Accounting at Principia College, and is currently a Professor of Marketing in the George Herbert Walker School of Business & Technology at Webster University based in St. Louis, Missouri (USA) where he teaches Marketing Statistics, Marketing Research, and Pricing Strategies. He has written 60+ textbook supplements in Marketing and Management, published 20+ articles in professional journals, and presented 20+ papers at professional meetings. He holds a B.S. in Mathematics from John Carroll University, both an M.A. in Education and a Ph.D. in Educational Psychology from Stanford University, and an M.B.A. from The University of Missouri-St. Louis.