• Install R Studio For Mac
• Download Updated R And R Studio For Mac Osx
• Download Updated R And R Studio For Macs

Install R on Mac. Step – 1: Go to CRAN R Project Website. Step – 2: Click on the Download for (Mac) OS X link. Step – 3: Click on the link for the pkg file of the latest R version and save it. Step – 4: Double click the downloaded file and follow installation instructions. Install RStudio on Mac OS X. Step – 1: With the r. R-Studio is a family of powerful and cost-effective undelete and data recovery software. Empowered by new unique data recovery technologies, it is the most comprehensive data recovery solution for recovering files from from FAT12/16/32, NTFS, exFAT, NTFS5 (created or updated by Windows NT/2000/ XP/ 2003/ Vista/ 2008/ 7/ 8/8.1/ 10), ReFS (Resilient File System, a new local file system. Mac version of updateR function: the UpdateR package. Since I am a lazy programmer and generally a devote of the great thesis introduced within The pragmatc programmer, I decided to develop updateR, a package that let’s you update your R version from R itself just running one line of code.

R and RStudio are both free, open-source software, available for all commonly used operating systems. R is developed cooperatively and noncommercially under the auspices of the Free Software Foundation; RStudio is a commercial product.

R and RStudio install in the standard manner on each of Windows, macOS, and Linux systems. System-specific instructions for installing R are given below. Regardless of your operating system, you should install R before installing RStudio.

If you wish to install the R Commander graphical user interface for R (used only in lecture 1), you may want also to consult the R Commander installation instructions (especially if you run into difficulties).

Please read and follow these instructions carefully. Installation assistance will also be availabile from the instructor (John Fox) and teaching assistant (Allison Leanage) prior to the start of thelecture series and during office hours.

Installing R on Windows

Visit the Comprehensive R Archive Network (CRAN) and select a mirror site; a list of CRAN mirrors appears at the upper left of the CRAN home page. I suggest that you use the 0-Cloud mirror, which is the first on the list. Click on the link Download R for Windows, which appears near the top of the page; then click on install R for the first time, and subsequently on Download R x.y.z for Windows (where x.y.z is the current version of R, which is R 4.0.2 at the start of the lectures series). Once it is downloaded, double-click on the R installer. You may take all of the defaults, but I suggest that you make the following modifications:

Instead of installing R in the standard location, C:Program FilesRR-x.y.z, I suggest that you use C:RR-x.y.z. Again, x.y.z is the current version of R. This will allow you to install packages in the main R library without running R with administrator privileges and may avoid problems that sometimes occur when there are spaces in paths.

In the Startup options screen, I suggest that you select Yes (customized startup). Then select the SDI (single-document interface) in preference to the default MDI (multiple-document interface); feel free to make other changes, but you may take all the remaining defaults.

Building Packages Under Windows, etc. (Optional)

If you wish to build packages, or use compiled C, C++, or Fortran code in R, or use the rstan package for Bayesian inference, you will have to install some additional software and properly configure your Windows system. You do not have to be able to build R packages in order to install pre-built Windows binary packages from CRAN, so these steps are generally unnecessary unless you plan to write your own packages, use compiled code, or use rstan. None of these topics are covered in the lecture series.

Click on the Rtools link on the R for Windows CRAN page. Download the current version of the Rtools installer and run it. You may take all of the other defaults. An additional necessary step is to add the Rtools usrbin subdirectory to your system path; for example, if Rtools is installed in c:rtoolsxy (which is the standard location for version xy of Rtools), then you would add c:rtoolsxyusrbin; to your system path. Type this location carefully, including the terminating semicolon -- you don't want to mess up your path.

An alternative, and possibly safer, procedure for specifying the path to Rtools is described on the Rtools webpage.

If you want to be able to build R packages outside of RStudio, also add c:RR-x.y.zbin; to the path (assuming that you installed R in the location that I suggested).

If you want to be able to build PDF help files for packages, download and install the MiKTeX LaTeX system; there is also a link to MiKTeX on the Building R for Windows page. Installing MiKTeX will also allow you to create Sweave and knitr LaTeX documents in RStudio, and to compile R Markdown documents directly to PDF files.

Installing R on macOS

Visit the Comprehensive R Archive Network (CRAN) and select a mirror site; a list of CRAN mirrors appears at the upper left of the CRAN home page. I suggest that you use the 0-Cloud mirror, which is the first on the list. Click on the link Download R for MacOS X, which appears near the top of the page; then click on R-x.y.z.pkg (where x.y.z is the current version of R -- R 4.0.2 at the start of the lectures series), which assumes that you are using macOS 10.11 (El Capitan) or higher. You'll also find older versions of R if you have an older version of macOS. Note: As a general matter, you're probably better off updating your macOS to the current version.

Once it is downloaded, double-click on the R installer. You may take all of the defaults.

Building Packages Under macOS, etc. (Optional)

If you wish to build packages, or use compiled C, C++, or Fortran code in R, or use the rstan package for Bayesian inference, you must install the Apple Xcode developer tools. None of these topics is covered in the lecture series. For macOS 10.7 (Lion) or higher, you can install Xcode for free from the App Store. For earlier versions of macOS, Xcode can be installed from your system DVD or downloaded from the Apple developer website. You do not need Xcode to install pre-built macOS binary packages from CRAN, so this step is unnecessary unless you plan to write your own packages, use compiled code, or use the rstan Bayesian estimation package.

Some R packages include Fortran, C, or C++ code; to build such packages, you will have to install compilers for these languages.The C and C++ compilers are included in the Apple Xcode tools, but you will have to separately download and install a Fortran compiler.

If you want to be able to build PDF help files, download and install the MacTeX LaTeX system. Installing MacTeX will also allow you to create Sweave and knitr LaTeX documents in RStudio, and to compile R Markdown documents directly to PDF files.

Installing X-Windows on macOS (Optional)

Some R software (e.g., my Rcmdr package) makes use of the Tcl/Tk graphical-user-interface (GUI) builder via the tcltk package to create point-and-click interfaces and to display GUI elements such as progress bars. To use the tcltk package, which is a standard part of the R distribution, you must have the X11 windowing system installed on your Mac. Some other packages that don't use Tcl/Tk, such as the rgl package for dynamic 3D graphics, also require X11.

Install R Studio For Mac

Check to see whether the X11 windowing system (X Windows) has already been installed on your computer. If you wish, it should do no harm to skip this step and simply go to the next step to install XQuartz.

For OS X 10.6 and 10.7, the file X11.app should appear in the Utilities folder under Applications in the finder. This application should always be installed under OS X 10.7.

For OS X 10.8 or higher, the file is named XQuartz.app and is no longer included with the operating system. XQuartz.app may also be installed in OS X 10.6 or 10.7.

Note that if you upgrade macOS, you will have to reinstall XQuartz even if you installed it previously.

You may also issue the command capabilities('X11') at the R command prompt. If the response is TRUE then X11 is installed.

If neither X11.app nor XQuartz.app is installed, install XQuartz from http://xquartz.macosforge.org. As mentioned, it should do no harm to install XQuartz even if you have X11 currently installed.

1. Download the disk image (dmg) file for XQuartz.

2. When you open this file by double-clicking on it, you'll find XQuartz.pkg; double-click on it to run the installer, clicking through all the defaults.

3. Important: After the installer runs, you'll have to log out and back on to your macOS account, or just reboot your Mac. Also, on first use, XQuartz builds a cache of fonts and so initial performance may be slow; this problem should go away after a short period of time.

Installing R on Linux Systems

Visit the Comprehensive R Archive Network (CRAN) and select a mirror site near you; a list of CRAN mirrors appears at the upper left of the CRAN home page. I suggest that you use the 0-Cloud mirror, which is the first on the list. Click on the link Download R for Linux, which appears near the top of the page. R is available for several Linux distributions (Debian, RedHat, SUSE, and Ubuntu); select your distribution, and proceed as directed.

If you have a Linux or Unix system that's not compatible with one of these distributions, you will have to compile R from source code; the procedure for doing so is described in the R FAQ (frequently asked questions) list.

Installing RStudio

Go to the RStudio download page, select the free version of RStudio Desktop, scroll down to Installers for Supported Platforms, and click on the link to the appropriate installer for your operating system (Windows, macOS, or Linux distro). Visit the RStudio IDE home page for more information about RStudio.

Once it is downloaded, run the RStudio installer and take all of the defaults: In Windows, double-click on the RStudio installer to start the installation; in macOS, double-click on the downloaded RStudio disk-image file, and drag the RStudio icon to the Applications folder.

When you first run RStudio, it should detect your R installation and start the R console. To configure RStudio to your taste, select Tools > Global Options (Windows) or RStudio > Preferences (macOS) from the RStudio menus. In particular, I suggest that on the General options screen you deselectRestore .RData into workspace at startup, and set Save workspace to .RData on exit to Never.

If you encounter difficulties, consult the RStudio troubleshooting guide. or seek help from John or Allison.

Installing R Packages for the Lecture Series

Once you have installed R and RStudio, you can install additional packages required for the lecture series by typing the following command at the > command prompt in the R Console (and pressing the Enter or return key):

install.packages(c('car', 'data.table', 'effects', 'knitr', 'lme4', 'rgl', 'rmarkdown', 'sfsmisc', 'tidyverse'))

You can simply copy and paste this command from these installation instructions. Alternatively, you can install packages from the RStudio Packages tab. Be aware that, depending on the speed of your internet connection, it may take some time to download and install these packages and their dependencies.

If you wish to use the R Commander, also issue the command install.packages('Rcmdr'). On first use, via the library('Rcmdr') command in R, the R Commander will offer to install additional packages that it needs.

If you want to try using C++ code within R (not discussed in the lecture series), also install the Rcpp package, install.packages('Rcpp'). You'll also have to install a C++ compiler, as described in the sections above on building packages under Windows and macOS.

Similarly, if you want to use the Stan Bayesian statistical software via the rstan package (not discussed in the lecture series), you'll have to install the package by the command install.packages('rstan'), and also install a C++ compiler.

This directory contains binaries for a base distribution and packages to run on Mac OS X (release 10.6 and above). Mac OS 8.6 to 9.2 (and Mac OS X 10.1) are no longer supported but you can find the last supported release of R for these systems (which is R 1.7.1) here. Releases for old Mac OS X systems (through Mac OS X 10.5) and PowerPC Macs can be found in the old directory.

Note: CRAN does not have Mac OS X systems and cannot check these binaries for viruses.Although we take precautions when assembling binaries, please use the normal precautions with downloaded executables.

Download Updated R And R Studio For Mac Osx

Package binaries for R versions older than 3.2.0 are only available from the CRAN archive so users of such versions should adjust the CRAN mirror setting (https://cran-archive.r-project.org) accordingly.

R 4.0.3 'Bunny-Wunnies Freak Out' released on 2020/10/10

Please check the MD5 checksum of the downloaded image to ensure that it has not been tampered with or corrupted during the mirroring process. For example type
openssl sha1 R-4.0.3.pkg
in the Terminal application to print the SHA1 checksum for the R-4.0.3.pkg image. On Mac OS X 10.7 and later you can also validate the signature using
pkgutil --check-signature R-4.0.3.pkg

Latest release:

R-4.0.3.pkg (notarized and signed) SHA1-hash: 8402f586aef1fdb12c6e34c73b286f87318fb1be (ca. 85MB)	R 4.0.3 binary for macOS 10.13 (High Sierra) and higher, signed and notarized package. Contains R 4.0.3 framework, R.app GUI 1.73 in 64-bit for Intel Macs, Tcl/Tk 8.6.6 X11 libraries and Texinfo 6.7. The latter two components are optional and can be ommitted when choosing 'custom install', they are only needed if you want to use the tcltk R package or build package documentation from sources. Note: the use of X11 (including tcltk) requires XQuartz to be installed since it is no longer part of OS X. Always re-install XQuartz when upgrading your macOS to a new major version. Important: this release uses Xcode 10.1 and GNU Fortran 8.2. If you wish to compile R packages from sources, you will need to download and GNU Fortran 8.2 - see the tools directory.
NEWS (for Mac GUI)	News features and changes in the R.app Mac GUI
Mac-GUI-1.73.tar.gz SHA1-hash: 7f4b1d050757ce78545bdeb9d178a69d13046aa1	Sources for the R.app GUI 1.73 for Mac OS X. This file is only needed if you want to join the development of the GUI, it is not intended for regular users. Read the INSTALL file for further instructions.
Note: Previous R versions for El Capitan can be found in the el-capitan/base directory. Binaries for legacy OS X systems:
R-3.6.3.nn.pkg (signed) SHA1-hash: c462c9b1f9b45d778f05b8d9aa25a9123b3557c4 (ca. 77MB)	R 3.6.3 binary for OS X 10.11 (El Capitan) and higher, signed package. Contains R 3.6.3 framework, R.app GUI 1.70 in 64-bit for Intel Macs, Tcl/Tk 8.6.6 X11 libraries and Texinfo 5.2. The latter two components are optional and can be ommitted when choosing 'custom install', they are only needed if you want to use the tcltk R package or build package documentation from sources.
R-3.3.3.pkg MD5-hash: 893ba010f303e666e19f86e4800f1fbf SHA1-hash: 5ae71b000b15805f95f38c08c45972d51ce3d027 (ca. 71MB)	R 3.3.3 binary for Mac OS X 10.9 (Mavericks) and higher, signed package. Contains R 3.3.3 framework, R.app GUI 1.69 in 64-bit for Intel Macs, Tcl/Tk 8.6.0 X11 libraries and Texinfo 5.2. The latter two components are optional and can be ommitted when choosing 'custom install', it is only needed if you want to use the tcltk R package or build package documentation from sources. Note: the use of X11 (including tcltk) requires XQuartz to be installed since it is no longer part of OS X. Always re-install XQuartz when upgrading your OS X to a new major version.
R-3.2.1-snowleopard.pkg MD5-hash: 58fe9d01314d9cb75ff80ccfb914fd65 SHA1-hash: be6e91db12bac22a324f0cb51c7efa9063ece0d0 (ca. 68MB)	R 3.2.1 legacy binary for Mac OS X 10.6 (Snow Leopard) - 10.8 (Mountain Lion), signed package. Contains R 3.2.1 framework, R.app GUI 1.66 in 64-bit for Intel Macs. This package contains the R framework, 64-bit GUI (R.app), Tcl/Tk 8.6.0 X11 libraries and Texinfop 5.2. GNU Fortran is NOT included (needed if you want to compile packages from sources that contain FORTRAN code) please see the tools directory. NOTE: the binary support for OS X before Mavericks is being phased out, we do not expect further releases!

The new R.app Cocoa GUI has been written by Simon Urbanek and Stefano Iacus with contributions from many developers and translators world-wide, see 'About R' in the GUI.

Subdirectories:

Download Updated R And R Studio For Macs

tools	Additional tools necessary for building R for Mac OS X: Universal GNU Fortran compiler for Mac OS X (see R for Mac tools page for details).
base	Binaries of R builds for macOS 10.13 or higher (High Sierra)
contrib	Binaries of package builds for macOS 10.13 or higher (High Sierra)
el-capitan	Binaries of package builds for OS X 10.11 or higher (El Capitan build)
mavericks	Binaries of package builds for Mac OS X 10.9 or higher (Mavericks build)
old	Previously released R versions for Mac OS X

You may also want to read the R FAQ and R for Mac OS X FAQ. For discussion of Mac-related topics and reporting Mac-specific bugs, please use the R-SIG-Mac mailing list.

Information, tools and most recent daily builds of the R GUI, R-patched and R-devel can be found at http://mac.R-project.org/. Please visit that page especially during beta stages to help us test the Mac OS X binaries before final release!

Package maintainers should visit CRAN check summary page to see whether their package is compatible with the current build of R for Mac OS X.

Binary libraries for dependencies not present here are available from http://mac.R-project.org/libs and corresponding sources at http://mac.R-project.org/src.

Last modified: 2020/10/10, by Simon Urbanek