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Primer for Data Analytics and Graduate Study in Statistics

Language EnglishEnglish
Book Paperback
Book Primer for Data Analytics and Graduate Study in Statistics Douglas Wolfe
Libristo code: 37220867
Publishers Springer Nature Switzerland AG, September 2021
This book is specially designed to refresh and elevate the level of understanding of the foundationa... Full description
? points 147 b
60.72 €
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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.

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About the book

Full name Primer for Data Analytics and Graduate Study in Statistics
Author Douglas Wolfe
Language English
Binding Book - Paperback
Date of issue 2021
Number of pages 233
EAN 9783030474812
ISBN 303047481X
Libristo code 37220867
Publishers Springer Nature Switzerland AG
Weight 379
Dimensions 155 x 235 x 14

Categories

Economics, Finance, Business & Management > Industry & industrial studies > Media, entertainment, information & communication industries > Information technology industries
Mathematics & Science > Mathematics > Applied mathematics > Stochastics
Computing & Information Technology > Computer science > Human–computer interaction > Information architecture
Reference, Information & Interdisciplinary subjects > Research & information: general > Information theory
Economics, Finance, Business & Management > Business & Management > Business mathematics & systems
Mathematics & Science > Mathematics > Probability & statistics
Computing & Information Technology > Computer programming / software engineering > Algorithms & data structures
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