Updated: Mon, 10/07/2024 - 21:42

From Saturday, Oct. 5 through Tuesday, Oct. 8, the Downtown and Macdonald Campuses will be open only to McGill students, employees and essential visitors. Many classes will be held online. Remote work required where possible. See Campus Public Safety website for details.


Du samedi 5 octobre au mardi 8 octobre, le campus du centre-ville et le campus Macdonald ne seront accessibles qu’aux étudiants et aux membres du personnel de l’Université McGill, ainsi qu’aux visiteurs essentiels. De nombreux cours auront lieu en ligne. Le personnel devra travailler à distance, si possible. Voir le site Web de la Direction de la protection et de la prévention pour plus de détails.

Event

SIS Seminar Series - Using R for research, part 2: analysing and visualising data

Monday, October 28, 2019 12:00to14:00
Peel 3661 3661 rue Peel, Montreal, QC, H3A 1X1, CA
sis_seminar_series_c_trudeau_oct_28

R is a powerful data analysis tool for researchers. It’s a statistical programming language that is supported by a free, open-source editing environment (RStudio) that is dedicated to building an inclusive and diverse R community. Like all tools, R has a learning curve and it can be difficult to know where to start. This seminar is a guided introduction to R and some of the ways that it can be used to support research in information studies.

No previous knowledge of statistics or of programming is assumed. An interest in quantitative research would be helpful. This workshop will be hands-on using examples of data taken from public sources, so please bring your laptops with you. As well, please install R and RStudio (in that order) before coming to the workshop. The process takes about 20 minutes in all. To install R: https://cran.r-project.org/. For RStudio: https://rstudio.com/products/rstudio/download/ (choose the free RStudio desktop version).

Part 2 will introduce the following concepts. (You do not need to have participated in Part 1, but it is recommended.)

  • Basic data analysis (descriptive statistics, correlations)
  • Visualizing data using ggplot
  • Simple regression (time and interest permitting)
  • Visualizing regressions using ggplot (time and interest permitting)
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