Data Analysis and Interpretation¶
Interpretation of data can be both statistical and graphical. Below is a list of the most commonly used programming languages for analyzing and interpreting data.
- R (Part 1 of download: to select the OS download of UofM’s closest CRAN for retrieving coding packages).
- RStudio (Part 2 of download: to visualize code via user-friendly GUI).
Tutorials and Resources¶
- This video is a great resource for a brief yet thorough introduction to the basics of R for beginners.
- Use R cheat sheets for quick reference in data manipulation, using dplyr, and graphing with ggplot2.
For graduate or research personnel at the University of Manitoba, here is a list of resources offered by various faculties:
- R for Environmental Research
- R Data Analysis and Visualization Workshop
- Data Science NEXUS workshops
- R for beginners
For an instructive video series on Python watch Ilkka Kokkarinen’s lectures from Ryerson University in The Chang School of Continuing Education; an introductory course to Computer Science.