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https://github.com/dcs-training/from-spss-to-r-how-to-make-your-statistical-analysis-reproducible

Comfortable/aware of how to run your stats in SPSS? Curious to learn how to run them in R? You've come to the right place. Go to the readme file
https://github.com/dcs-training/from-spss-to-r-how-to-make-your-statistical-analysis-reproducible

data-analysis data-visualisation data-wrangling good-practices-digital-research r rmarkdown spss statistics

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Comfortable/aware of how to run your stats in SPSS? Curious to learn how to run them in R? You've come to the right place. Go to the readme file

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README 

        
# From SPSS to R: How to Make Your Statistical Analysis Reproducible



Comfortable/aware of how to run your stats in SPSS? Curious to learn how to run them in R? You've come to the right place.



In part 1 of this course, we will learn to:

- Download and navigate R.

- Work with R markdown documents.

- Conduct our trusty SPSS analysis through R.



In part 2 of this course, we will learn to:

-   Upload your own data to R.

-   Create a data tidying script.

-   Learn how to save your tidied data (in case you want to transfer analysis to other software/supervisors).

-   A reminder of our analyses.

-   Learn how to create APA ready analysis outputs - no more copy and pasting our results!



The material in this repo was developed and curated by Rhys Davies. All material collected here is free to use but is covered by a License: [![License: CC BY-NC 4.0](https://licensebuttons.net/l/by-nc/4.0/80x15.png)](https://creativecommons.org/licenses/by-nc/4.0/) license



## R Setting Up



You can either run the code on your own machine or through Posit (RStudio Online IDE) or if you are part of the University of Edinburgh through [Noteable](https://noteable.edina.ac.uk/).

Below are the instructions for setting up. 



### On Posit



1. Go to https://posit.cloud/

2. Signup either via Gmail or GitHub

3. Go on New Project

4. New Project from Git Repository

5. Copy and Paste this repository URL [https://github.com/DCS-training/From-SPSS-to-R-How-to-Make-Your-Statistical-Analysis-Reproducible](https://github.com/DCS-training/From-SPSS-to-R-How-to-Make-Your-Statistical-Analysis-Reproducible) as the Repository URL

6. The Project directory name will filled in automatically

7. Navigate to the rmd file you want to explore



### Locally



- R and RStudio are separate downloads and installations. R is the underlying statistical computing environment, but using R alone is no fun. RStudio is a graphical integrated development environment (IDE) that makes using R much easier and more interactive. You need to install R before you install RStudio. After installing both programs, you will need to install some specific R packages within RStudio. Follow the instructions below for your operating system, and then follow the instructions to install the needed packages(below)



_Windows_



- If you already have R and RStudio installed



  - Open RStudio, and click on "Help" > "Check for updates". If a new version is available, quit RStudio, and download the latest version for RStudio.

  - To check which version of R you are using, start RStudio and the first thing that appears in the console indicates the version of R you are running. Alternatively, you can type `sessionInfo()`, which will also display which version of R you are running. Go on the [CRAN website](https://cran.r-project.org/bin/windows/base/) and check whether a more recent version is available. If so, please download and install it. You can [check here](https://cran.r-project.org/bin/windows/base/rw-FAQ.html#How-do-I-UNinstall-R_003f) for more information on how to remove old versions from your system if you wish to do so.



- If you don't have R and RStudio installed



  - Download R from the [CRAN website](https://cran.r-project.org/bin/windows/base/release.htm).

  - Run the `.exe` file that was just downloaded

  - Go to the [RStudio download page](https://www.rstudio.com/products/rstudio/download/#download)

  - Under _Installers_ select **RStudio x.yy.zzz - Windows Vista/7/8/10** (where x, y, and z represent version numbers)

  - Double click the file to install it

  - Once it's installed, open RStudio to make sure it works and you don't get any error messages.



_macOS_



- If you already have R and RStudio installed



  - Open RStudio, and click on "Help" > "Check for updates". If a new version is available, quit RStudio, and download the latest version for RStudio.

  - To check the version of R you are using, start RStudio and the first thing that appears on the terminal indicates the version of R you are running. Alternatively, you can type `sessionInfo()`, which will also display which version of R you are running. Go on the [CRAN website](https://cran.r-project.org/bin/macosx/) and check whether a more recent version is available. If so, please download and install it.



- If you don't have R and RStudio installed



  - Download R from the [CRAN website](https://cran.r-project.org/bin/macosx/).

  - Select the `.pkg` file for the latest R version

  - Double-click on the downloaded file to install R

  - It is also a good idea to install [XQuartz](https://www.xquartz.org/) (needed by some packages)

  - Go to the [RStudio download page](https://www.rstudio.com/products/rstudio/download/#download)

  - Under _Installers_ select **RStudio x.yy.zzz - Mac OS X 10.6+ (64-bit)** (where x, y, and z represent version numbers)

  - Double-click the file to install RStudio

  - Once it's installed, open RStudio to make sure it works and you don't get any error messages.



_Linux_



- Follow the instructions for your distribution from [CRAN](https://cloud.r-project.org/bin/linux), they provide information to get the most recent version of R for common distributions. For most distributions, you could use your package manager (e.g., for Debian/Ubuntu run `sudo apt-get install r-base`, and for Fedora `sudo yum install R`), but we don't recommend this approach as the versions provided by this are usually out of date. In any case, make sure you have at least R 3.5.1.

- Go to the [RStudio download page](https://www.rstudio.com/products/rstudio/download/#download)

- Under _Installers_ select the version that matches your distribution, and install it with your preferred method (e.g., with Debian/Ubuntu `sudo dpkg -i rstudio-x.yy.zzz-amd64.deb` at the terminal).

- Once it's installed, open RStudio to make sure it works and you don't get any

  error messages.



Once you have R and R Studio installed, open R Studio



1.  Go to File>New Project> Version Control >Git

2.  Enter the Repository URL [https://github.com/DCS-training/From-SPSS-to-R-How-to-Make-Your-Statistical-Analysis-Reproducible](https://github.com/DCS-training/From-SPSS-to-R-How-to-Make-Your-Statistical-Analysis-Reproducible) 

3.  Select the Name for the directory project and where to save it

4.  Press Create Project



### On Noteable

1. Go to https://noteable.edina.ac.uk/login

2. Login with your EASE credentials

3. Select RStudio as a personal notebook server and press start

4. Go to File >New Project>Version Control>Git

5. Copy and Paste this repository URL [https://github.com/DCS-training/From-SPSS-to-R-How-to-Make-Your-Statistical-Analysis-Reproducible](https://github.com/DCS-training/From-SPSS-to-R-How-to-Make-Your-Statistical-Analysis-Reproducible) as the Repository URL

6. The Project directory name will filled in automatically but you can change it if you want your folder in Notable to have a different name

7. Decide where to locate the folder. By default, it will locate it in your home directory 

8. Press Create Project