Primer for Data Analytics and Graduate Study in Statistics - Rilegato

Wolfe, Douglas; Schneider, Grant

Rilegato

ISBN 10: 303047478X ISBN 13: 9783030474782

Casa editrice: Springer Nature, 2020

Riassunto

This book is specially designed to refresh and elevate the level of understanding of the foundational background in probability and distributional theory required to be successful in a graduate-level statistics program. Advanced undergraduate students and introductory graduate students from a variety of quantitative backgrounds will benefit from the transitional bridge that this volume offers, from a more generalized study of undergraduate mathematics and statistics to the career-focused, applied education at the graduate level. In particular, it focuses on growing fields that will be of potential interest to future M.S. and Ph.D. students, as well as advanced undergraduates heading directly into the workplace: data analytics, statistics and biostatistics, and related areas.<br>

Su questo libro

Informazioni sull?autore

<b>Douglas A. Wolfe</b> is Chair and Professor Emeritus in the Department of Statistics at Ohio State University. His recent publications include <i>Intuitive Introductory Statistics </i>(Springer 2017) and <i>Nonparametric Statistical Methods, 3rd Edition</i> (2014). He is an elected fellow of the American Statistical Association and of the Institute of Mathematical Statistics. <p><b>Grant Schneider</b> is the Head of Upstart Columbus and a Data Scientist at Upstart, the leading AI lending platform. Before returning to Ohio in 2019, he spent the previous five years working on Upstart’s Data Science team in Silicon Valley building AI models used to extend credit to borrowers left behind by traditional models. Dr. Schneider obtained his Bachelors, Masters, and Ph.D. degrees from The Ohio State University and is the co-author of <i>Intuitive Introductory Statistics </i>(Springer 2017). He has also authored the <i>NSM3 </i>and <i>IIS</i> R packages.</p>

Dalla quarta di copertina

This book is specially designed to refresh and elevate the level of understanding of the foundational background in probability and distributional theory required to be successful in a graduate-level statistics program. Advanced undergraduate students and introductory graduate students from a variety of quantitative backgrounds will benefit from the transitional bridge that this volume offers, from a more generalized study of undergraduate mathematics and statistics to the career-focused, applied education at the graduate level. In particular, it focuses on growing fields that will be of potential interest to future M.S. and Ph.D. students, as well as advanced undergraduates heading directly into the workplace: data analytics, statistics and biostatistics, and related areas.

Dettagli dell'edizione

• Editore: Springer Nature
• Data di pubblicazione: 2020
• Lingua: Inglese
• ISBN 10: 303047478X
• ISBN 13: 9783030474782
• Rilegatura: Copertina rigida
• Numero edizione: 1
• Numero di pagine: 233
• Contatto del produttore: non disponibile
• Persona responsabile: CMN Printpool Inh. Mathis Neumann; https://www.also.com/ec/cms5/en_6000/6000/index.jsp; ; Friedrich-Karl-Str. 9; Hamburg; Germania