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Advances in Systems Analysis, Software Engineering, and High Performance Computing Ser.: Comparative Approaches to Using R and Python for Statistical Data Analysis by Rui Sarmento and Vera Costa (2017, Hardcover)

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About this product

Product Identifiers

PublisherIGI Global Scientific Publishing

ISBN-10168318016X

ISBN-139781683180166

eBay Product ID (ePID)14038748712

Product Key Features

Number of Pages200 Pages

LanguageEnglish

Publication NameComparative Approaches to Using Rand Python for Statistical Data Analysis

SubjectProbability & Statistics / General, Data Visualization, Statistics, Programming Languages / Python

Publication Year2017

TypeTextbook

AuthorRui Sarmento, Vera Costa

Subject AreaMathematics, Computers, Business & Economics

SeriesAdvances in Systems Analysis, Software Engineering, and High Performance Computing Ser.

FormatHardcover

Dimensions

Item Length10 in

Item Width7 in

Additional Product Features

Intended AudienceCollege Audience

LCCN2016-050989

Dewey Edition23

IllustratedYes

Dewey Decimal519.50285/5133

SynopsisThe application of statistics has proliferated in recent years and has become increasingly relevant across numerous fields of study. With the advent of new technologies, its availability has opened into a wider range of users. Comparative Approaches to using R and Python for Statistical Data Analysis is a comprehensive source of emerging research and perspectives on the latest computer software and available languages for the visualization of statistical data. By providing insights on relevant topics, such as inference, factor analysis, and linear regression, this publication is ideally designed for professionals, researchers, academics, graduate students, and practitioners interested in the optimization of statistical data analysis., The application of statistics has proliferated in recent years and has become increasingly relevant across numerous fields of study. With the advent of new technologies, its availability has opened into a wider range of users. Comparative Approaches to Using R and Python for Statistical Data Analysis is a comprehensive source of emerging research and perspectives on the latest computer software and available languages for the visualization of statistical data. By providing insights on relevant topics, such as inference, factor analysis, and linear regression, this publication is ideally designed for professionals, researchers, academics, graduate students, and practitioners interested in the optimization of statistical data analysis.

LC Classification NumberQA276.45.R3 S27