R for Data Analysis: Useful Tools for Otolaryngologists and Researchers

PROGRAM DESCRIPTION: Please download R and RStudio prior to this session.

Limited by Microsoft Excel for statistical analysis? No or limited access to SPSS, SAS, or Stata ?

R is an increasingly popular statistical software that acts as an alternative to traditional statistical packages. R is an open-source and free statistical programming language and software environment widely used among statisticians for data analysis. User-created packages extend the capabilities of R to allow for specialized statistical analysis, data visualization, and machine learning applications. R has numerous applications in domains like healthcare, academics, consulting, finance, media, and many more. SPSS, SAS, and Stata offer statistical analysis, but they require a license and have high costs. While R has a steep learning curve, it has numerous advantages including very large range of functions (over 2,000 packages), very good community support, extensive help resources freely available, and compatible on multiple platforms (e.g. Windows, Macintosh, UNIX, Linux).
Otolaryngologists must be able to interpret medical literature in order to deliver effective, evidence-based care. Furthermore, a knowledge of modern data analysis may help otolaryngologists both interpret data as well as analyze them. Currently, many otolaryngologists understand how to interpret medical literature, but lack the knowledge on how to perform statistical analysis beyond simple rudimentary techniques. By providing attendees with a working knowledge of R, this session will enable cutting edge data analysis. During the session, attendees will be introduced to R software and programming, and go through a live R simulation of data cleaning and analysis using sample data. At the conclusion of the program, the attendees will be able to have a basic understanding of R, how to import a dataset, find and load R packages, perform simple data ‘tidying’, and perform some visualizations and statistical analysis. We hope to provide attendees with the basic knowledge and resources so that they can start using R for data analysis in their own research pursuits.

OUTCOME OBJECTIVE 1: Attendees will understand the basics of R and RStudio, and be able to identify helpful online resources.

OUTCOME OBJECTIVE 2: Attendees will be able to load datasets into RStudio, find and install appropriate packages, and prepare or tidy data for analysis.

OUTCOME OBJECTIVE 3: Attendees will perform some data visualizations (e.g. boxplots, bar graphs, histograms) and statistical analysis (e.g. student’s t test, Chi square test, correlation test).

BACKGROUND STATEMENT: Many otolaryngologists lack the ability to perform sophisticated data analysis. By providing instruction in R, attendees will be equipped with state-of-the-art tools and skillset to become more comfortable and independent in scholarly pursuits.