thomas-keller / ranalysisworkshop2018

Code, slides and information for the 2018 USF Data Analysis Using R Workshop

Data Analysis Using R Workshop (2018)

Code, slides and information for the 2018 USF Data Analysis Using R Workshop

Description

R is a free and flexible software program, which is common in various data science fields. This workshop will introduce undergraduate and graduate-level students to R and how to implement R and various popular packages to perform important data visualizations and analyses for research.

Organization

The workshop will consist of two parts over 5 days. The first part will be four days, from November 5 - November 9, of 2-hour sessions that will be available as webinars. The last day will be an in-person capstone project that will take place at Cooper Hall (room 255) on USF campus from 10 am - 12:30 pm. The daily information sessions will provide students with an overview of selected topics, interactive examples and discussion, as well as examples from current users on how they utilize R in their work every day. Each day will be centered around a tenant of data science. The first day will introduce the basics of R and importing and cleaning data. Day two will focus on data visualization methods and day three on modeling (data mining and statistical modeling) the data. The fourth day will cover machine learning and Shiny. For the capstone project, participants will choose from 3 subject areas: health, finance, and environment, and complete a project that incorporates all the lessons from the previous days. At the end of the last day, participants who attend each day of lecture and the capstone project will receive a certificate of completion.

Webinar videos will be available online. All code and slides from the sessions will be posted here 24 hours in advance.

Sponsors and collaborators

This workshop is sponsored by the American Statistical Association USF chapter, Interdisciplinary Data Sciences Consortium, Tampa Bay R useRs and the International Federation of Non-linear Analysts.