R and Python Workshops

This 3-day hands-on and in-person workshop introduces participants to R by providing instruction and hands-on exercises. Participants will gain understanding of basic workflows in R, including data manipulation, graphics, and programming. We will emphasize the tidyverse family of packages in R. No prior experience with R will be assumed.

Learning objectives:

• Introduction to R—why use it, user interface (R Studio) and basic data structures
• Overview of data management techniques using the tidyverse package
• Learn elementary graphic functions for data visualization
• Learn how to import and export datasets

Get started with R by registering here.

This 3-day hands-on and in-person workshop shows you how to do basic statistical analyses using R. We emphasize intuition over math as we review key statistical concepts and how they relate to the most commonly used basic statistical methods: t-tests, chi-square tests, linear and logistic regression analyses. More advanced methods may be introduced, including: multiple regression and analysis of variance. Previous introductory experience with R, and experience with basic statistical ideas, is required.

Learning objectives:

• Ability to conduct basic statistical analyses of your own data using R
• Increased understanding of how and when to apply different statistical methods
• Greater comfort interpreting statistical results and checking their assumptions
• Greater appreciation for situations where more advanced techniques might be appropriate

Dive deeper with R by registering here.

This 3-day, hands-on workshop, teaches you more advance techniques that will make your data wrangling easier and more effective. Picking up where our Using R for Absolute Beginners ended, we will focus on effective techniques for preparing your data to be easy to analyse. Specific topics include wrangling data with missing values, calculating derived fields in your data, joining multiple pieces of data together. Previous introductory experience with R is required for this workshop.

Learning objectives:

• Practice loading, cleaning and reshaping data originally collected and stored in .CSV and Excel files.
• Learn the basic principles of “tidy data” and to make your data analysis work much easier.
• Write scripts for a basic data analysis project – load, clean, prep, summarize, plot, and analyze.

Learn how to make your data cleaner by registering here.

This 5-day hands-on workshop, jointly presented by CHI and the Children’s Hospital Research Institute of Manitoba (CHRIM), will introduce participants to Python using a combination of instruction and hands-on exercises.

Learning objectives:

• Acquire a solid understanding of Python programming fundamentals
• Learn data processing techniques using the Pandas library
• Gain skills in data visualization and descriptive data analysis
• Adopt best practices in programming, debugging, and version control
• Learn how integrated development environments (IDEs) and computational notebooks enhance productivity and reproducibility

Get started with Python by registering here.