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
|Publisher:||Springer International Publishing|
|Product dimensions:||6.10(w) x 9.25(h) x 0.02(d)|
About the Author
At the beginning of his academic career, Prof. Thomas J. Quirk spent six years in educational research at The American Institutes for Research and Educational Testing Service. He 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. This is Professor Quirk’s ninth statistics book with Springer.
Meghan H.Quirk holds both a Ph.D. in Biological Education and an M.A. in Biological Sciences from the University of Northern Colorado (UNC) and a B.A. 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 and has presented papers at the Shortgrass Steppe Symposium in Fort Collins, Colorado, the Long-term Ecological Research All Scientists Meeting in Estes Park, Colorado, and participated in the NSF Site Review of the Shortgrass Steppe Long Term Ecological Research in Nunn, Colorado. She was a National Science Foundation Fellow GK-12, and currently teaches in Bailey, 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 is currently a District Wildlife Manager with the Colorado Division of Parks and Wildlife.
Table of Contents Sample Size, Mean, Standard Deviation, and 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 Meansfor Independent Groups.-Correlation and Simple Linear Regression.