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    Learning RStudio for R Statistical Computing Mark P.J. van der Loo, RStudio Inc, Edwin de Jonge, Mark van der Loo

    (ebook) (audiobook) (audiobook) Książka w języku 1
    Learning RStudio for R Statistical Computing Mark P.J. van der Loo, RStudio Inc, Edwin de Jonge, Mark van der Loo - okladka książki

    Learning RStudio for R Statistical Computing Mark P.J. van der Loo, RStudio Inc, Edwin de Jonge, Mark van der Loo - okladka książki

    Learning RStudio for R Statistical Computing Mark P.J. van der Loo, RStudio Inc, Edwin de Jonge, Mark van der Loo - audiobook MP3

    Learning RStudio for R Statistical Computing Mark P.J. van der Loo, RStudio Inc, Edwin de Jonge, Mark van der Loo - audiobook CD

    Autorzy:
    Mark P.J. van der Loo, RStudio Inc, Edwin de Jonge, Mark van der Loo
    Wydawnictwo:
    Packt Publishing (Z chęcią przeczytam książkę w języku polskim)
    Ocena:
    Bądź pierwszym, który oceni tę książkę
    Stron:
    126
    Dostępne formaty:
         PDF
         ePub
         Mobi
    Data is coming at us faster, dirtier, and at an ever increasing rate. The necessity to handle many, complex statistical analysis projects is hitting statisticians and analysts across the globe. This book will show you how to deal with it like never before, thus providing an edge and improving productivity.
    Learning RStudio for R Statistical Computing will teach you how to quickly and efficiently create and manage statistical analysis projects, import data, develop R scripts, and generate reports and graphics. R developers will learn about package development, coding principles, and version control with RStudio.
    This book will help you to learn and understand RStudio features to effectively perform statistical analysis and reporting, code editing, and R development.
    The book starts with a quick introduction where you will learn to load data, perform simple analysis, plot a graph, and generate automatic reports. You will then be able to explore the available features for effective coding, graphical analysis, R project management, report generation, and even project management.
    Learning RStudio for R Statistical Computing is stuffed with feature-rich and easy-to-understand examples, through step-by-step instructions helping you to quickly master the most popular IDE for R development.

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    O autorach książki

    Mark van der Loo obtained his PhD at the Institute for Theoretical Chemistry at the University of Nijmegen (The Netherlands). Since 2007 he has worked at the statistical methodology department of the Dutch official statistics office (Statistics Netherlands). His research interests include automated data cleaning methods and statistical computing. At Statistics Netherlands he is responsible for the local R center of expertise, which supports and educates users on statistical computing with R. Mark has been teaching R for several years and coauthored a number of R packages that are available via CRAN: editrules, deducorrect, rspa, and extremevalues. A list of publications can be found via https://www.markvanderloo.eu.
    Edwin de Jonge is a statistical consultant (methodologist) at Statistics Netherlands, which is the office that produces all official statistics of the Netherlands (census, labor force, environmental etc). He is consulted on data visualization, big data, clustering and R programming problems.



    Having a background in theoretical and computational physics he has a research interest in computational statistics, including numerical methods. Edwin is (co)author of several R software packages on data cleaning, large data sets and visualization (editrules, deducorrect, tabplotd3, ffbase and whisker) and has authored a book on using RStudio.

    Currently he is co-authoring a book for Wiley "Data cleaning with applications in R". He is an experienced R trainer.



    His main research focuses on using visualization methods for exploratory data analysis including visualization of uncertainty and semantic technologies. Recent projects include:



    - StatMine, visual exploration of output-data

    - Visualisation techniques for Big Data

    - Datacleaning algorithms

    - Processing and analyzing Big data.
    Mark van der Loo obtained his PhD at the Institute for Theoretical Chemistry at the University of Nijmegen (The Netherlands). Since 2007 he has worked at the statistical methodology department of the Dutch official statistics office (Statistics Netherlands). His research interests include automated data cleaning methods and statistical computing. At Statistics Netherlands he is responsible for the local R center of expertise, which supports and educates users on statistical computing with R. Mark has been teaching R for several years and coauthored a number of R packages that are available via CRAN: editrules, deducorrect, rspa, and extremevalues. A list of publications can be found via https://www.markvanderloo.eu.

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