This workshop will be held live on April 6, 13, 20, 2021 (5:30PM-8:00PM) OVERVIEW This workshop will explore both the design side and the coding side of creating visualizations in R. The first session will introduce best practices for designing effective visualizations, and learners will put these into practice in the next two sessions to [....]
This workshop will be held live on May 4, 11, 18, 2021 (5:30PM-8:00PM) Overview This workshop will provide an introduction to working with text data in R and explore various approaches to analyzing text data. The first session will cover principles for wrangling text data as well as some basic text mining applications. The subsequent [....]
IMMU 102 - Emerging Coronaviruses. Emerging microbial pathogens are of increasing concern both nationally and internationally with the potential to cause widespread morbidity and mortality at an unprecedented level. The current outbreak of COVID-19 provides evidence that unknown microbial agents have the ability to emerge from their natural hosts to spread, adapt, and cause disease [....]
This workshop will be held live on June 1, 8, 15, 2021 (5:30PM-8:00PM) Overview In this workshop, learners will learn the basics of how to use R to wrangle data, create visualizations, and conduct exploratory analyses. The workshop will use the popular “tidyverse” suite of packages and will also teach learners the concept of tidy [....]
We will work in RStudio, an integrated development environment (IDE) built specifically for R. A copy of all the scripts used in class to import and tidy data, create visualizations, and perform analyses will be provided to each participant at the end of the training. Who Should Attend? Those new to programming and data science [....]
Target Audience Researchers who understand statistical concepts and have perhaps conducted analyses using Excel, SPSS, or similar, but have little to no experience using R. Upon Completing The Workshop, Attendees will have the Confidence, Knowledge, and Resources to: 1) Create R projects to organize data and code 2) Write R scripts to perform full data [....]
