Data tools¶

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.

Python
- For a more user-friendly interface that assists with updates and packages, use Anaconda Navigator . Click here for installation instructions.
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).
Matlab

Tutorials and Resources¶

R¶

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:

Python¶

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.