The ability to create professional grade graphics is of key importance for scientific communication. The R programming package offers a powerful, flexible, and free platform which can be used to produce publication-quality graphics. This short course will introduce R techniques to produce several statistical graphs including histograms, bar plots, box plots, scatter plots and 3D contour plots among others. Syntax to control colors, plotting characters, axes, legends, and labels will be covered, and users will learn to write high resolution graphics to the file type of their choice. Two data sets will be used to demonstrate R’s graphical capabilities. The National Longitudinal Mortality Survey includes nearly a million records with 38 measurements each. A classic prostate data set (Stamey, et al. 1989) includes 9 clinical measurements on 97 men. The course format includes lecture and computer laboratory components. The lecture component will cover pros and cons of various graphics and approaches, and the computer portion will allow attendees to write, modify, and execute R codes to produce graphics based on these data.
This session is the third entry in a three course series which assumes no previous coding experience in R or any other language. The intended audience for this course includes researchers who want to gain basic exposure to R with the ultimate goal of incorporating R into their research programs.
Stamey TA, Kabalin JN, McNeal JE, Johnstone IM, Freiha FS, Redwine EA, and Yang N: Prostate specific antigen in the diagnosis and treatment of adenocarcinoma of the prostate. II. Radical prostatectomy treated patients. J Urol.141: 1076-1083, 1989.
This course was also taught on Tuesday, July 9th.