Statistics for Data Scientists: An Introduction to Probability, Statistics, and Data Analysis (Undergraduate Topics in Computer Science) - Softcover

Kaptein, Maurits; Van Den Heuvel, Edwin

 
9783030105303: Statistics for Data Scientists: An Introduction to Probability, Statistics, and Data Analysis (Undergraduate Topics in Computer Science)
Softcover
ISBN 10: 303010530X ISBN 13: 9783030105303
Verlag: Springer, 2022

Inhaltsangabe

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.

Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.

Über die Autorin bzw. den Autor

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.

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. 

Von der hinteren Coverseite

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.

„Über diesen Titel“ kann sich auf eine andere Ausgabe dieses Titels beziehen.

Verlag
Springer
Erscheinungsdatum
2022
Sprache
Englisch
ISBN 10 
303010530X
ISBN 13 
9783030105303
Einband
Taschenbuch
Auflage
1
Anzahl der Seiten
348
Kontakt zum Hersteller
ProductSafety@springernature.com
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