An Introduction to R Programming

Jeffery Miecnikowski, Daniel Gaile, Rachael Hageman Blair
March 26, 2015

Department of Biostatistics
School of Public Health and Health Professions, SUNY at Buffalo

Preliminary Instructions

Jeffery Miecnikowski, PhD

  • PhD Statistics 2006 Carnegie Mellon University
  • Associate Dean for Faculty Affairs and Diversity, SPHHP
  • Associate Professor, Department of Biostatistics
  • Instructor for STA 511 and STA 521
  • Co-authored several R packages

Daniel Gaile, PhD

  • PhD Statistics 2003 Texas A&M University
  • Assistant Professor, Department of Biostatistics
  • Director, Statistical Consulting Laboratory
  • Instructor for STA 502 and STA 525
  • Co-authored several R packages
  • R User since ~1998

Rachael Hageman-Blair, PhD

Overview of Talk

This workshop is divided into three parts:

  • Part I [Miecznikowski] : An overview and introduction to basic features of R.
  • Part II [Gaile]: A very brisk overview of basic testing, visualization, dimension reduction and model building in R. Presented in the context of a STA525 (i.e.,'Bioinformatics') example.
  • Part III [Hageman Blair]: An introduction to subset selection and model building in R. Presented in the context of STA545/546 (i.e., “Data Mining”) examples.

.Rpres Presentations

  • These particular slides are admittedly plain. However, they showcase the .Rpres format available in R (and made all the more convenient in RStudio).
  • Let's have a look at the IntroRmod0.Rpres file to see how these slides were generated.
  • Open your own .Rpres file
  • Explore the “Authoring R Presentations” help file.
  • Bottomline: the R Markdown format provides for a convenient mechanism to quickly author presentation content.

Data Science and Statistics

  • Before we begin discussing R, we would like to address the attendees that are interested in pursuing educations related to “data science”.
  • The Department of Biostatistics offers courses for undergraduate, graduate and non-matriculated students.
  • But why should a student that is interested in data science, consider taking courses in statistics?

Be a Unicorn!