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Autor Tópico: R Programming For beginners (2023)  (Lida 53 vezes)

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R Programming For beginners (2023)
« em: 04 de Março de 2023, 13:00 »

R Programming For beginners (2023)
Last updated 02/2023
Duration: 1h 54m | Video: .MP4, 1280x720 30 fps | Audio: AAC, 48 kHz, 2ch | Size: 724 MB
Genre: eLearning | Language: English[Auto]

Learn R Programming for Data Science and Data Analysis

What you'll learn
Install R and RStudio
Create R script
Create new R Projects
Install and load packages
Clean data with R
Pipe functions into datasets
Visualize your data using base R graphics
Analyse Data
Create objects (variables)
Requirements
No experience required
Description
R is a programming language and software environment for statistical computing and graphics supported by the R Foundation for Statistical Computing.

The R language is widely used among statisticians and data miners for developing statistical software and data analysis . R is an integrated suite of software facilities for data manipulation, calculation and graphical display. It includes

• an effective data handling and storage facility,

• a suite of operators for calculations on arrays, in particular matrices,

• a large, coherent, integrated collection of intermediate tools for data analysis,

• graphical facilities for data analysis and display either on-screen or on hardcopy, and

• a well-developed, simple and effective programming language which includes conditionals, loops, user-defined recursive functions and input and output facilities.

RStudio is an integrated development environment for R, a programming language for statistical computing and graphics. It is available in two formats: RStudio Desktop is a regular desktop application while RStudio Server runs on a remote server and allows accessing RStudio using a web browser.
R is installed on your computer and uses your personal computer resources to process R programming language. RStudio integrates with R as an IDE (Integrated Development Environment) to provide further functionality. RStudio combines a source code editor, build automation tools and a debugger.
In this course we will setup an R environment and perform data analysis and visualisation.

Who this course is for
Beginners to R

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