Statistics for Data Scientists: An Introduction to Probability, Statistics, and Data Analysis

by Maurits Kaptein, Edwin van den Heuvel

Overview

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.

Product Details

ISBN-13:	9783030105303
Publisher:	Springer International Publishing
Publication date:	02/03/2022
Series:	Undergraduate Topics in Computer Science
Edition description:	1st ed. 2022
Pages:	321
Product dimensions:	6.10(w) x 9.25(h) x (d)

About the Author

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.

Table of Contents

1 A First Look at Data.- 2 Sampling Plans and Estimates.- 3 Probability Theory.- 4 Random Variables and Distributions.- 5 Estimation.- 6 Multiple Random Variables.- 7 Making Decisions in Uncertainty.- 8 Bayesian Statistics.

Editorial Reviews

Having taught data analytics at the introductory graduate level, I welcome the authors’ textbook as an essential resource for training well-grounded entry-level data scientists. … A data scientist shall provide competent data science professional services to a client. … Training in both the theory and practice of data analytics is a requirement for such competence. The authors’ textbook definitely provides a valuable resource for such training.” (Harry J. Foxwell, Computing Reviews, July 7, 2022)

From the Publisher