Overview
- Written in a step-by-step, instructional format, with accompanying Excel screenshots, enabling readers 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 physical sciences. 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
Part of the book series: Excel for Statistics (EXCELSTAT)
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Table of contents (8 chapters)
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Front Matter
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Back Matter
Keywords
About this book
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.
Reviews
Authors and Affiliations
About the authors
Prof. Tom J. Quirk is a Professor Emeritus of Marketing in The Walker School of Business & Technology at Webster University in St. Louis, Missouri (US). He has published over 20 articles in professional journals, and presented more than 20 papers at professional conferences. 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.
Dr. Meghan H. Quirk holds a PhD in Biological Education and an MA in Biological Sciences from the University of Northern Colorado (UNC) and a BA in Biology and Religion at Principia College in Elsah, Illinois. She has done research on foodweb dynamics at Wind Cave National Park in South Dakota and research in agro-ecology in Southern Belize. She has co-authored an article on shortgrass steppe ecosystems in Photochemistry & Photobiology. She was a National Science Foundation Fellow GK-12, and currently is a public school administrator in Parker, Colorado.
Howard F. Horton holds an MS in Biological Sciences from the University of Northern Colorado (UNC) and a BS in Biological Sciences from Mesa State College. He has worked on research projects in Pawnee National Grasslands, Rocky Mountain National Park, Long-Term Ecological Research at Toolik Lake, Alaska, and Wind Cave, South Dakota. He has co-authored articles in The International Journal of Speleology and The Journal of Cave and Karst Studies. He was a National Science Foundation Fellow GK-12 and a District Wildlife manager with the Colorado Division of Parks and Wildlife. He is currently the Angler Outreach Coordinator with the Colorado Division of Parks and Wildlife.
Bibliographic Information
Book Title: Excel 2019 for Physical Sciences Statistics
Book Subtitle: A Guide to Solving Practical Problems
Authors: Thomas J. Quirk, Meghan H. Quirk, Howard F. Horton
Series Title: Excel for Statistics
DOI: https://doi.org/10.1007/978-3-030-63238-0
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021
Softcover ISBN: 978-3-030-63237-3Published: 09 March 2021
eBook ISBN: 978-3-030-63238-0Published: 08 March 2021
Series ISSN: 2570-4605
Series E-ISSN: 2570-4613
Edition Number: 2
Number of Pages: XIX, 242
Number of Illustrations: 5 b/w illustrations, 161 illustrations in colour
Topics: Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences, Mathematical Applications in the Physical Sciences, Computer Appl. in Social and Behavioral Sciences