Excel 2019 for Engineering Statistics: A Guide to Solving Practical Problems: Excel for Statistics
Autor Thomas J. Quirken Limba Engleză Paperback – 10 apr 2020
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.
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Specificații
ISBN-13: 9783030392772
ISBN-10: 3030392775
Pagini: 250
Ilustrații: XVII, 250 p. 166 illus., 161 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.36 kg
Ediția:2nd ed. 2020
Editura: Springer International Publishing
Colecția Springer
Seria Excel for Statistics
Locul publicării:Cham, Switzerland
ISBN-10: 3030392775
Pagini: 250
Ilustrații: XVII, 250 p. 166 illus., 161 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.36 kg
Ediția:2nd ed. 2020
Editura: Springer International Publishing
Colecția Springer
Seria Excel for Statistics
Locul publicării:Cham, Switzerland
Cuprins
Preface.- Acknowledgements.- 1 Sample Size, Mean, Standard Deviation, and Standard Error of the Mean.- 2 Random Number Generator.- 3 Confidence Interval About the Mean Using the TINV Function and Hypothesis Testing.- 4 One-Group t-Test for the Mean.- 5 Two-Group t-Test of the Difference of the Means for Independent Groups.- 6 Correlation and Simple Linear Regression.- 7 Multiple Correlation and Multiple Regression.- 8 One-Way Analysis of Variance (ANOVA).- Appendix A: Answers to End-of-Chapter Practice Problems.- Appendix B: Practice Test.- Appendix C: Answers to Practice Test.- Appendix D: Statistical Formulas.- Appendix E: t-table.- Index.
Notă biografică
At the beginning of his academic career, Thomas J. Quirk spent six years performing educational research at The American Institutes for Research and Educational Testing Service. He then taught Social Psychology, Educational Psychology, Social Research Methods, General Psychology, Marketing, Management, and Accounting at Principia College. He is currently a Professor Emeritus of Marketing in The Walker School of Business & Technology at Webster University based in St. Louis, Missouri (USA), where he taught 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 BS in Mathematics from John Carroll University, both an MA in Education and a PhD in Educational Psychology from Stanford University, and an MBA from The University of Missouri-St. Louis.
Textul de pe ultima copertă
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.
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.
Caracteristici
Written in a step-by-step, instructional format, using the Excel steps with their accompanying color screenshot figures to show the reader what should be happening on the reader's computer monitor, enabling them to solve statistics problems on their own Contains forty (40) statistics problems (as well as answers in chapter appendices) that are integrally related to courses in engineering and engineering statistics. These are provided at the end of each chapter, and in a practice test at the end of the volume Utilizes a comprehensible style, intended to be more digestible than the typical statistics text