Introduction to R

2:00pm to 4:00pm PST each day | Online

Session 1: Tuesday April 6 | Session 2: Thursday April 8 
Session 3: Tuesday April 13 | Session 4: Thursday April 15


Overview

R is rapidly growing adoption through research and government institutions. R is a free software program and most RStudio products are free as well with no monthly subscriptions or licensing costs.

This webinar-based course focuses on how to use R and R Studio and the basic terminology and concepts for working in the R environment. You will learn how to create reproducible work flows in R using R Markdown, which is “an authoring framework for data science”. This software feature allows you to generate narrative and text within an R Markdown document, while including any code and scripts alongside your narrative. This means your work will always be reproducible and if you need to generate the same report every week, you can make minimal changes to your existing R Markdown.

To ensure you can stay on track with your R work, the course also focuses on best practices for managing an R Project and utilizes the tidyverse packages. These packages are designed to work well together for data importing, data manipulation and data cleaning, modeling, data visualization, working with dates and strings and more!

Register nowThe best way to learn how to use R is to practice, make mistakes, learn and repeat. This course will help you get started on the right path!


This course is designed for:

  • A person without programming skills or little-to-no R experience who wants to learn or understand how R can be useful to them.
  • A proficient Excel/SPSS/SAS user working in public health who wants to switch to R.

Topics covered

  1. Moving from Excel to Reproducible work
  2. Introduction to R and R Studio
  3. R Projects and Reproducible Workflows
  4. Introduction to R Markdown for reproducible reports (word, pdf, html)
  5. R Data Types
  6. Data Transformation, working with dates, missing values and recoding values
  7. Brief Data Visualization and summary tables
  8. Joins
  9. Functions

R installation support

Pre-course R software installation support will be offered prior to the start of the first session. Registrants will receive step by step documentation for installation. A drop-in session will also be scheduled for Friday April 2nd 2:00pm to 3:00pm PST for related assistance as needed.

Workshop fees

  • Regular rate: $260
  • Student Rate: $160

Webinar Format

The interactive webinar software will provide remote access for students to view the instructor’s screen, listen to the lecture in real time, and ask questions. The instructor will provide lecture slides (PowerPoint) and required readings prior to the start of the webinar. For practice between webinar sessions and for follow up study, students will also receive training data and programming code for R.

Course developer

Lauren Yee

Lauren Yee is multifaceted researcher and data person. She has worked in academia, public health, and the consulting industry. Her interdisciplinary background has provided her with the experience of working with many different types of datasets, methodologies and their related data quality issues and methods of visualization. She has taught workshops on GIS and spatial modeling, data management in R, data visualization in R, and advanced R Markdown. Her research interests include: spatial epidemiology, Ecohealth approach, determinants of health, white nose syndrome and zoonoses.

 

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