Happy Holidays—Our $30 Gift Card just for you, and books ship free! Shop now>>

Undergraduate Topics in Computer Science
cover

Statistics for Data Scientists

An introduction to probability, statistics, and data analysis

Authors: Kaptein, Maurits, van den Heuvel, Edwin

  • Provides an accessible introduction to applied statistics for data scientists by uniquely combining hands-on exercises with mathematical theory and an introduction to probability theory
  • Contains modern statistical methods that are often deemed “advanced material”; it covers bootstrapping, Bayesian decision theory, equivalence testing, study designs with association measures and statistical modelling
  • Introduces sampling and uncertainty; where most textbooks either ignore the underlying mathematical theory or introduce solely the asymptotic theory, this introduces statistical inference in a natural way, using finite samples and real data
see more benefits

Buy this book

eBook  
  • ISBN 978-3-030-10531-0
  • Digitally watermarked, DRM-free
  • Included format:
  • ebooks can be used on all reading devices
Softcover ca. 46,79 €
price for Spain (gross)
  • Due: July 27, 2020
  • ISBN 978-3-030-10530-3
  • Free shipping for individuals worldwide
  • The final prices may differ from the prices shown due to specifics of VAT rules
About this Textbook

This book provides an undergraduate introduction to analysing data for data science, computer science, and quantitative social science students. It uniquely combines a hands-on approach to data analysis – supported by numerous real data examples and reusable [R] code – with a rigorous treatment of probability and statistical principles. 

Where contemporary undergraduate textbooks in probability theory or statistics often miss applications and an introductory treatment of modern methods (bootstrapping, Bayes, etc.), and where applied data analysis books often miss a rigorous theoretical treatment, this book provides an accessible but thorough introduction into data analysis, using statistical methods combining the two viewpoints. The book further focuses on methods for dealing with large data-sets and streaming-data and hence provides a single-course introduction of statistical methods for data science.

About the authors

Prof. Dr. Edwin van den Heuvel works on statistical methods for analyzing cross-sectional and longitudinal data from experimental and observational studies in the domain of health and life sciences. He has been teaching many different topics on statistics to (PhD, master, and bachelor) students from different backgrounds (medicine, engineering, mathematics, etc.) He is full-time professor in statistics at Eindhoven University of Technology and has affiliations at other universities. He publishes mostly in peer-reviewed influential statistical, epidemiological, and medical journals.  Prof. Dr. Maurits Kaptein works on statistical methods for sequential experimentation. He has extensive experience in research and education in the fields of statistics, machine learning, and research methodology. Maurits works for the Jheronimus Academy of Data Science and for the University of Tilburg. His work has been published in influential journals such as Bayesian Analysis and the Journal of Interactive Marketing.

Buy this book

eBook  
  • ISBN 978-3-030-10531-0
  • Digitally watermarked, DRM-free
  • Included format:
  • ebooks can be used on all reading devices
Softcover ca. 46,79 €
price for Spain (gross)
  • Due: July 27, 2020
  • ISBN 978-3-030-10530-3
  • Free shipping for individuals worldwide
  • The final prices may differ from the prices shown due to specifics of VAT rules

Recommended for you

Loading...

Bibliographic Information

Bibliographic Information
Book Title
Statistics for Data Scientists
Book Subtitle
An introduction to probability, statistics, and data analysis
Authors
Series Title
Undergraduate Topics in Computer Science
Copyright
2020
Publisher
Springer International Publishing
Copyright Holder
Springer Nature Switzerland AG
eBook ISBN
978-3-030-10531-0
Softcover ISBN
978-3-030-10530-3
Series ISSN
1863-7310
Edition Number
1
Number of Illustrations
53 b/w illustrations
Topics