Before we meet for our first class there are few things you should try at home to get started.
This semester students will be submitting their work as github repositories. Follow these steps to test the github pipeline to make sure it is working:
If you are unable to install R, RStudio, and Github desktop on your computer, then an alternative option is to use RStudio Cloud, which runs in your web-browser. RStudio Cloud also works with Github.com. Follow these steps, and/or watch the screencast for this method. Note, these instructions were slightly modified from Symphony Yu’s blog post.
You can now use R Studio in the cloud. Any new files that you make will be saved to the project folder you made in R Studio Cloud. However, these files will not be “pushed” to Github.com. In order to push the files to Github.com, follow the next steps:
Replace email@example.com inside the quotations with the email associated with your Github.com account
git config --global user.email "firstname.lastname@example.org"
Replace Your Name inside the quotations with your Github username.
git config --global user.name "Your Name"
In the terminal, type the following, but replace YourUsername and YourRepo with your Github username and Github repository name (as it is written in your Github repository URL):
git config remote.origin.url email@example.com:YourUsername/YourRepo.git
You should now be able to use the git tab in R studio to push and pull files between R Studio Cloud and Github.com. See examples in the screen cast.
A quick attempt to explain why I think it is totally worth it to learn R for data-analysis, and for psychologists in general.
We will take a number of different approaches to using R to learn about statistics this semester. One of the approaches will be to learn about basic coding/scripting in R, which can become an entire course on its own. This video gives an impression of what coding looks and feels like in R Studio, and introduces some basic coding concepts such as variables, logic, loops, and functions.
In addition to lab material, I will be posting additional screencasts here that provide more angles on learning R basics. For example, it can be useful to have specific problems thta you are trying to solve, and then set yourself the goal of figuring out how to solve the problems in R. I have a created a list of problems here https://crumplab.github.io/programmingforpsych/programming-challenges-i-learning-the-fundamentals.html. Some of the problems will be assigned in lab. Here, my plan to do some live coding, showing ways that I solve these problems.