LISA Statistics Short Course: Statistical Analysis in R
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 2013 Schedule:
Monday, June 10: Structural Equation Modeling (SEM) Using AMOS;
Monday, June 17: Designing Experiments and Collecting Useful Data*;
Monday, June 24 & Tuesday, June 25: Basics of R;
Monday, July 1 & Tuesday, July 2: Statistical Analysis in R;
Monday, July 8 & Tuesday, July 9: Graphing with R;
Monday, July 15: SAS Programming I;
Tuesday, July 16: SAS Programming II;
Monday, July 22: Model selection in R featuring the lasso;
*This course will be held in Fralin Auditorium, all other courses are in 3060 Torgersen Hall.
Monday, July 1 and Tuesday, July 2, 4:00-6:00 pm;
Instructor: Ning Wang;
Location: 3060 Torgersen Hall;
Title: Statistical Analysis in R;
R is a free computing and graphical software/environment for statistical analysis. This short course describes basic statistical analysis in R using two data sets. The 1974 Motor Trend Car Road Tests dataset which comprises fuel consumption and 10 aspects of automobile design and performance for 32 automobiles will be used to illustrate the analyses. Analyses will also be performed on the National Longitudinal Mortality Survey which includes nearly a million records with 38 measurements each. Analyses described include t-tests, ANOVA, linear regression, and nonparametric tests. The course format includes a lecture portion covering statistical concepts, and the computer laboratory component covers usage of R to perform the analyses described above. The attendee can write, modify, and execute R codes for the statistical analysis.
This session is the second in a three-course series, which assumes no previous coding experience in R or any other language. Experience using R or attending Part I of this series is suggested but not required for this course. The intended audience for this course includes researchers who want to gain basic exposure to statistical analysis in R with the ultimate goal of incorporating R into their research programs. A schedule of available LISA short courses may be found here: www.lisa.stat.vt.edu/?q=short_courses
R can be downloaded here: www.r-project.org
RStudio can be downloaded here: http://rstudio.org/download/desktop
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