Welcome

Welcome to my blog - R with Alex (or Rawlex for short). In this blog, I will (hopefully) acquaint you with R and its application for data analysis, with multiple examples. Most of my examples will be drawn from datasests from Psychology, because that is my domain of specialty. However, you can apply these principles to apply to your own analysis and answer your own research questions from other disciplines.

Don’t fear

It is normal to feel overwhelmed and fearful as you start learning a new language. The process is similar to learning a foreign language. In fact, think of R as a foreign language. Without any knowledge, foreign language can look and sound like gibberish to you. After learning and consistently practicing, you start to understand. Better yet, you will be able to communicate with others using that language. R is the same. It may be a little difficult at the beginning but you will get yourself familiar with it in no time. In fact, students who have started learning R showed neutral to positive attitudes towards R. Many find R valuable and they feel competent (which you are!) after being able to use R (Counsell & Cribbie, 2020; Tucker et al., 2022). The key is to sustain your engagement with R overtime (Tucker et al., 2022). In other words, practice, practice, and practice (Tucker et al., 2022).

Why R

These are just a few reasons:

• Free and open-source
• User-created packages make it easy to conduct even more complicated analysis.
• Flexible and wide range of uses
• Better data visualization (the graphs look really pretty!)
• Highly valued skill in academia and industry

However, unlike other (paid) services (e.g., SPSS), R do not have a point-and-click system, but it is a powerful tool to conduct more complicated analysis efficiently and quickly. Once you learn the basics, you can teach yourself to do even more with R.

So, if this sounds like something you need, let’s get started!