Introduction to R

R is a free, open-source statistical programming language used to manipulate, analyze, and visualize data. The flexibility of R allows large amounts of data to be processed and represented in ways that spreadsheet programs cannot. This introductory, hands-on workshop provides a brief overview of how R works and what it is capable of. No prior experience with R or programming languages is required.

Visualizing Data in R

R is a free, open-source statistical programming language used to manipulate, analyze, and visualize data. In this hands-on workshop, users will be introduced to R packages used for data visualization. This session includes data visualization exercises utilizing a sample data set. Prior experience with R or completion of Ginn Library’s Introduction to R workshop is recommended but not required.

Introduction to R

R is a free, open-source statistical programming language used to manipulate, analyze, and visualize data. The flexibility of R allows large amounts of data to be processed and represented in ways that spreadsheet programs cannot. This introductory, hands-on workshop provides a brief overview of how R works and what it is capable of. No prior experience with R or programming languages is required.

Getting the Most Out of JumboSearch

This session will go through how to get better results using the JumboSearch tool as well as how to easily download a custom list of the articles, books and reports retrieved. JumboSearch is the main access point to Tufts' print and online book collections, most online journal subscriptions, as well as most report content from other databases. While it offers an easy single box search option, refining your search will deliver much better results.

Register for this event on MyFletcher.

Visualizing Data in R

R is a free, open-source statistical programming language used to manipulate, analyze, and visualize data. In this hands-on workshop, users will be introduced to R packages used for data visualization. This session includes data visualization exercises utilizing a sample data set.  Prior experience with R or completion of Ginn Library’s Introduction to R workshop is recommended but not required.