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Excel 2016 for Human Resource Management Statistics: A Guide to Solving Practical Problems /
Tag	Description
020	$a9783319400631$9978-3-319-40063-1
082	$a519.5$223
099	$aOnline resource: Springer
100	$aQuirk, Thomas J.
245	$aExcel 2016 for Human Resource Management Statistics$h[EBook]$bA Guide to Solving Practical Problems /$cby Thomas J. Quirk, Julie Palmer-Schuyler.
260	$aCham :$bSpringer International Publishing :$bImprint: Springer,$c2016.
300	$aXVII, 258 p. 162 illus., 161 illus. in color.$bonline resource.
336	$atext$btxt$2rdacontent
337	$acomputer$bc$2rdamedia
338	$aonline resource$bcr$2rdacarrier
440	$aExcel for Statistics
505	$aIntroduction -- Sample size, mean, standard deviation, 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) -- Appendix A -- Appendix B -- Appendix C -- Appendix D -- Appendix E -- Index.
520	$aThis book shows the capabilities of Microsoft Excel in teaching human resource management statistics effectively. Similar to the previously published Excel 2013 for Human Resource Management Statistics, this book is a step-by-step exercise-driven guide for students and practitioners who need to master Excel to solve practical human resource management 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 human resource management courses. Its powerful computational ability and graphical functions make learning statistics much easier than in years past. However, Excel 2016 for Human Resource Management 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 human resource management 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 162 illustrations in color Suitable for undergraduate and graduate students At the beginning of his academic career, Prof. 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 Walker School of Business & Technology at Webster University based in St. Louis, Missouri (USA). 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. Prof. “J.P.” Palmer-Schuyler is currently an Associate Professor of Human Resource Management in the Walker School of Business and Technology at Webster University in St. Louis, Missouri, USA, where she teaches undergraduate Human Resource Management and Organizational Behavior. She received her MBA from the University of Nebraska-Lincoln and her Ph.D. from the University of Missouri-Columbia in Management. She has published articles in Academy of Business Disciplines Journal and Regional Business Review, and she has made conference presentations at the Academy of Management and Society for Advancement of Management.
538	$aOnline access to this digital book is restricted to subscription institutions through IP address (only for SISSA internal users)
700	$aPalmer-Schuyler, Julie.$eauthor.
710	$aSpringerLink (Online service)
830	$aExcel for Statistics
856	$uhttp://dx.doi.org/10.1007/978-3-319-40063-1