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Excel 2010 for Environmental Sciences Statistics: A Guide to Solving Practical Problems

Excel 2010 for Environmental Sciences Statistics: A Guide to Solving Practical Problems
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Field name Details
Dewey Class 519.5
Title Excel 2010 for Environmental Sciences Statistics ([EBook]) : A Guide to Solving Practical Problems / / by Thomas J. Quirk, Meghan H. Quirk, Howard F. Horton.
Author Quirk, Thomas J.
Added Personal Name Quirk, Meghan H. author.
Horton, Howard F. author.
Other name(s) SpringerLink (Online service)
Edition statement 1st ed. 2015.
Publication Cham : : Springer International Publishing : : Imprint: Springer, , 2015.
Physical Details XVII, 246 p. 162 illus., 2 illus. in color. : online resource.
Series Excel for Statistics
ISBN 9783319239712
Summary Note This is the first book to show the capabilities of Microsoft Excel to teach environmental sciences statistics effectively.  It is a step-by-step exercise-driven guide for students and practitioners who need to master Excel to solve practical environmental sciences 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 environmental science courses.  Its powerful computational ability and graphical functions make learning statistics much easier than in years past.  However, Excel 2010 for Environmental 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 environmental 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 162illustrations in color Suitable for undergrad uates or graduate students Prof. Thomas J. Quirk is currentlya Professor of Marketingin 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 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.  Dr. Meghan H.Quirk holds both a Ph.D. in Biological Education and an M.A. in Biological Sciences from the University ofNorthern Colorado (UNC) and a B.A. in Biology and Religion at Pri ncipia 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 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 Too lik 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 for Colorado Parks and Wildlife (USA).:
Contents note 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 Means for Independent Groups -- Correlation and Simple Linear Regression -- Multiple Correlation and Multiple Regression -- One-Way Analysis of Variance (ANOVA).
System details note Online access to this digital book is restricted to subscription institutions through IP address (only for SISSA internal users).
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