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Practical Statistics for Data Scientists: 50+ Essential Concepts Using R and Python

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Practical Statistics for Data Scientists: 50+ Essential Concepts Using R and Python

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Data Mining

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From the Preface

This book is aimed at the data scientist with some familiarity with the R and/or Python programming languages, and with some prior (perhaps spotty or ephemeral) exposure to statistics. Two of the authors came to the world of data science from the world of statistics, and have some appreciation of the contribution that statistics can make to the art of data science. At the same time, we are well aware of the limitations of traditional statistics instruction: statistics as a discipline is a century and a half old, and most statistics textbooks and courses are laden with the momentum and inertia of an ocean liner. All the methods in this book have some connection—historical or methodological—to the discipline of statistics. Methods that evolved mainly out of computer science, such as neural nets, are not included.

In all cases, this book gives code examples first in R and then in Python . In order to avoid unnecessary repetition, we generally show only output and plots created by the R code. We also skip the code required to load the required packages and data sets. You can find the complete code as well as the data sets for download at GitHub.

Two goals underlie this book:

To lay out, in digestible, navigable, and easily referenced form, key concepts from statistics that are relevant to data science.

To explain which concepts are important and useful from a data science perspective, which are less so, and why.

Product details

Data Science Statistics: R & Python -2
Main Specification
Marca by Peter Bruce (Author) or Andrew Bruce (Author) or Peter Gedeck (Author) & 0 more Format: Paperback
Data di pubblicazione 2020 or June 16
Articolo Peso 1.35 pounds
Product information
Lingua Inglese
Others
Tipo di prodotto Data Mining
Edizione 2nd
Editore O'Reilly Media
Lunghezza della stampa 360 pages
ISBN 92-78-0 149207294X
ISBN-13 978-1492072942
Dimensioni 7 x 0.9 x 9.1 inches
ISBN 92-78-0 149207294X
ISBN 92-77-1131 978-1492072942