Springer Series in Statistics
cover

Statistical Foundations, Reasoning and Inference

For Science and Data Science

Authors: Kauermann, Göran, Küchenhoff, Helmut, Heumann, Christian

  • Introduces statistics and data science students to classical and modern statistical concepts
  • Features detailed derivations and explanations of complex statistical methods
  • Includes statistical tools for applied data science, e.g. for missing data or causality
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eBook 93,08 €
price for Spain (gross)
  • The eBook version of this title will be available soon
  • Due: November 12, 2021
  • ISBN 978-3-030-69827-0
  • Digitally watermarked, DRM-free
  • Included format:
  • ebooks can be used on all reading devices
Hardcover 114,39 €
price for Spain (gross)
  • Due: November 12, 2021
  • ISBN 978-3-030-69826-3
  • Free shipping for individuals worldwide
  • Institutional customers should get in touch with their account manager
  • Covid-19 shipping restrictions
  • The final prices may differ from the prices shown due to specifics of VAT rules
About this Textbook

This textbook provides a comprehensive introduction to statistical principles, concepts and methods that are essential in modern statistics and data science. The topics covered include likelihood-based inference, Bayesian statistics, regression, statistical tests and the quantification of uncertainty. Moreover, the book addresses statistical ideas that are useful in modern data analytics, including bootstrapping, modeling of multivariate distributions, missing data analysis, causality as well as principles of experimental design. The textbook includes sufficient material for a two-semester course and is intended for master’s students in data science, statistics and computer science with a rudimentary grasp of probability theory. It will also be useful for data science practitioners who want to strengthen their statistics skills.

About the authors

Göran Kauermann is a Professor of Statistics at the Department of Statistics and Chair of the Elite Master’s Program in Data Science at the LMU Munich, Germany. He is a recognized expert in applied statistics. He previously served as Editor-in-Chief of AStA Advances in Statistical Analysis, a journal of the German Statistical Society.

Helmut Küchenhoff is a Professor of Statistics at the Department of Statistics and Head of the Statistical Consulting Unit (StaBLab) at the LMU Munich, Germany. He has extensive experience in working on practical statistical projects in science and industry. His teaching focuses on practical work, where students engage in practical projects with real-world problems.

Christian Heumann is a Professor at the Department of Statistics, LMU Munich, Germany, where he teaches students in both the Bachelor’s and Master’s programs. His research interests include statistical modeling, computational statistics and methods for missing data, also in connection with causal inference. Recently, he has begun exploring statistical methods in natural language processing.


Buy this book

eBook 93,08 €
price for Spain (gross)
  • The eBook version of this title will be available soon
  • Due: November 12, 2021
  • ISBN 978-3-030-69827-0
  • Digitally watermarked, DRM-free
  • Included format:
  • ebooks can be used on all reading devices
Hardcover 114,39 €
price for Spain (gross)
  • Due: November 12, 2021
  • ISBN 978-3-030-69826-3
  • Free shipping for individuals worldwide
  • Institutional customers should get in touch with their account manager
  • Covid-19 shipping restrictions
  • The final prices may differ from the prices shown due to specifics of VAT rules
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Bibliographic Information

Bibliographic Information
Book Title
Statistical Foundations, Reasoning and Inference
Book Subtitle
For Science and Data Science
Authors
Series Title
Springer Series in Statistics
Copyright
2021
Publisher
Springer International Publishing
Copyright Holder
The Editor(s) (if applicable) and The Author(s), under exclusive licence to Springer Nature Switzerland AG
eBook ISBN
978-3-030-69827-0
DOI
10.1007/978-3-030-69827-0
Hardcover ISBN
978-3-030-69826-3
Series ISSN
0172-7397
Edition Number
1
Number of Pages
XIII, 356
Number of Illustrations
77 b/w illustrations, 10 illustrations in colour
Topics