4:00pm to 6:00pm |
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LISA Statistics Short Course: Graphics in R
(Academic)
LISA SHORT COURSES IN STATISTICS
LISA (Virginia Tech's Laboratory for Interdisciplinary Statistical Analysis) is providing a series of evening short courses to help graduate students use statistics in their research. The focus of these two-hour courses is on teaching practical statistical techniques for analyzing or collecting data. See www.lisa.stat.vt.edu/?q=short_courses for instructions on how to REGISTER and to learn more.
Spring 2015 Schedule:
Monday & Tuesday, February 16 & 17: Basics of R;*
Monday & Tuesday, February 23 & 24: Graphics in R;*
Tuesday, March 3: Multivariate Analysis in R;
Tuesday, March 17: Designing Experiments;
Monday & Tuesday, March 23 & 24: Using ggplot2 to produce enhanced graphics in R;*
Tuesday, April 7: T-tests & ANOVA;
Tuesday, April 14: Solutions for Broken Linear Models;
*Two sessions to accommodate more attendees.
Tuesday, February 24;
Instructor: Adam Edwards;
Title: Graphics in R;
Course Information:
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, and scatter 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 data set and a data set about nutrition in breakfast cereals from DASL. 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 second part of 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.
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