About this product

Product Identifiers

PublisherSpringer International Publishing A&G

ISBN-10303010530X

ISBN-139783030105303

eBay Product ID (ePID)4038531393

Product Key Features

Number of PagesXxiv, 321 Pages

LanguageEnglish

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

SubjectProbability & Statistics / General, Computer Science, General

Publication Year2022

TypeTextbook

AuthorEdwin Van Den Heuvel, Maurits Kaptein

Subject AreaMathematics, Computers

SeriesUndergraduate Topics in Computer Science Ser.

FormatTrade Paperback

Dimensions

Item Weight18.8 Oz

Item Length9.3 in

Item Width6.1 in

Additional Product Features

Dewey Edition23

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)

Number of Volumes1 vol.

IllustratedYes

Dewey Decimal519.50285

Table Of Content1 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.

SynopsisThis 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., 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.

LC Classification NumberQA76.9.M35