Excel 2010 for environmental sciences statistics [electronic resource] : a guide to solving practical problems / Thomas J. Quirk, Meghan H. Quirk, Howard F. Horton.
2015
QA276
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Title
Excel 2010 for environmental sciences statistics [electronic resource] : a guide to solving practical problems / Thomas J. Quirk, Meghan H. Quirk, Howard F. Horton.
Author
ISBN
9783319239712 electronic book
3319239716 electronic book
9783319239699
3319239694
3319239716 electronic book
9783319239699
3319239694
Published
Cham : Springer, 2015.
Language
English
Description
1 online resource (xvii, 246 pages) : illustrations.
Item Number
10.1007/978-3-319-23971-2 doi
Call Number
QA276
Dewey Decimal Classification
519.5
Summary
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).
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text file PDF
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Series
Excel for statistics.
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Print version: 9783319239699
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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 Means for Independent Groups
Correlation and Simple Linear Regression
Multiple Correlation and Multiple Regression
One-Way Analysis of Variance (ANOVA).
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).