Thu, 02 July|
Online and face-to-face
Learn to love wrangling your data: A pragmatic introduction to R
This FOWI Academy session will introduce R: a powerful, free (and open source) programming language to help expand your capability in managing complex research questions and datasets.
Time & Location
02 July 2020, 1:00 pm – 3:00 pm
Online and face-to-face
About the Event
R is a powerful, free (and open-source) programming language that is gaining enormous traction, particularly in the social and behavioural sciences. This community growth has resulted in the release of hundreds of add-on packages that automate or simplify pain points in the research pipeline (e.g., data manipulation; model fitting; text processing). Learning R can dramatically improve your data processing efficiency and expand your capability to manage complex research questions and datasets. However, the process of starting to learn R from scratch can be daunting.
This FOWI Academy session will introduce R at a high level (i.e. conceptual). It will help researchers who have no R experience understand how to get started learning R, and importantly, provide motivation to do so. The session will begin with a brief overview of the language and common beliefs about R and programming. Next, a range of R features will be explored, referring to specific research and data problems. Resources and tips for continued learning, both structured and self-taught, will be provided throughout. The remainder of the session will be open for addressing questions and challenges people have experienced getting started with R (or related tools).
The session requires no prior experience with R and does not require any software. Individuals with intensive experience in R will probably still find the introduction section of interest.
About the presenter:
The presenter, Dr Michael-David Wilson is a Post-Doctoral Research Fellow at the Future of Work Institute and holds a PhD in Human Factors Psychology from the University of Western Australia (UWA). His research examines what factors underlie cognitive performance in complex and dynamic work environments over time (e.g., circadian rhythms, interruptions and workload). His work involves applying and developing computational statistical methods, with interest in hierarchical and dynamic Bayesian models.
This session will be delivered both online and face-to-face. To attend, it is essential that you RSVP. Please email Diane Garnham (Diane.Garnham@curtin.edu.au) and state your preference:
- Face-to-face (78 Murray Street, Perth): We have limited seats available due to social distancing rules. You will be placed in a ‘pool’ and be informed by Thursday June 25 whether you have a ticket.
- Online (via LiveStream): A link to the web stream will be emailed on the day along with instructions on how to access it.