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Statistical theory and formulas are explained in clear language without bogging you down in mathematical fine points
You will be told each step of the way, not only how to use Excel, but also why you are doing each step – so you can learn the techniques to apply Excel beyond this book
You will learn both how to write statistical formulas and how to use drop-down menus to have Excel create formulas for you
Includes 159 color screen shots so you can be sure you are performing Excel steps correctly
Each chapter includes specific objectives for each concept so you know the purpose of the Excel steps
Each chapter presents key steps needed to solve practical, easy-to-understand engineering science problems using Excel. In addition, three practice problems at the end of each chapter enable you to test your new knowledge. Answers to these problems appear in Appendix A
Practical examples of problems are taken from several areas in engineering
A “Practice Test” is given in Appendix B to test your knowledge at the end of the book. Answers appear in Appendix C
This book purposely does include a CD of Excel files. Instead, you’ll be shown how to create each Excel file yourself. In business, your colleagues will not give you an Excel file. You will be expected to create your own. This book will give you ample practice in developing this important skill
This book is a tool that can be used either by itself or along with any good statistics book
This is the first book to show the capabilities of Microsoft Excel to teach engineering statistics effectively. It is a step-by-step exercise-driven guide for students and practitioners who need to master Excel to solve practical engineering 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 engineering courses. Its powerful computational ability and graphical functions make learning statistics much easier than in years past. However, Excel 2010 for Engineering 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 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.
Includes 159 Illustrations in color
Suitable for upper undergraduates or graduate students
At the beginning of his academic career, Prof. 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.
Introduction.- Sample size, mean, standard deviation, standard error of the mean.- Random number generator.- Confidence interval about the mean using the TINV function and hypothesis testing.- One-group t-test for the mean.- Two-group t-test of the difference of the means for independent groups.- Correlation and simple linear regression.- Multiple correlation and multiple regression.- One-way analysis of variance (ANOVA).- Appendix A.- Appendix B.- Appendix C.- Appendix D.- Appendix E.- Index.