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LISA Statistics Short Course: Basics of 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.
Summer 2015 Schedule:
Wednesday, June 24: Designing Experiments;
Wednesday, July 1: Basics of R;
Wednesday, July 8: Generalized Linear Models (GLMs) and Categorical Data Analysis (CDA);
Wednesday, July 15: Graphics in R;
Wednesday, July 22: Multivariate Clustering in R;
Wednesday, July 29: Sample Size Calculations;
Wednesday, August 5: Using mixed effects models to quantify dependency among repeated measures;
Wednesday, July 1, 4:00-6:00 pm;
Location: 1080 Torgersen Hall;
Instructor: Ana Ortega;
Title: Basics of R;
R is a powerful, versatile, and free statistical programming language, which has become increasingly popular among industrial and academic data analysts. This introductory course covers programming basics in R, including the definition and manipulation of data objects, importing/exporting data, simple data summaries, simple graphs and if time permits, simple linear regression. These concepts will be illustrated using both the Home Prices Data and also the National Longitudinal Mortality Survey. The Home Prices Data is a random sample of records of resales of homes from the files maintained by the Albuquerque Board of Realtors and will be used to illustrate the basic principles listed above. The power of R will then be demonstrated by performing similar operations on the National Longitudinal Mortality Survey, which includes nearly a million records with 38 measurements each. The course format includes lecture and computer laboratory components and attendees will have the opportunity to write, modify, and execute R codes for these data.
This introductory session is 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. More experienced users may wish to skip this course and attend subsequent courses on statistical and graphical techniques using R.
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More information...
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540-231-8354