Date(s) - 10/02/2015 - 10/03/2015
Categories No Categories
Start Date: 10/2/2015
End Date: 10/3/2015
Temple University Center City
1515 Market Street
Taught by Richard Gonzalez, Ph.D.
This two-day seminar is designed to introduce the R package to those who already have some experience doing statistical analysis with another software package. At the conclusion of the seminar, you should be well equipped to do almost any standard analysis using R.
R has rapidly become a major tool for statistical analysis in both academia and industry. Journal articles on new statistical procedures often include R code so that readers can use the new technique immediately rather than wait years for it to be incorporated into traditional statistics packages. R produces amazing publication-quality graphics and plots, which are now being used by major news outlets such as the New York Times.
R can be easily modified so that you can organize output the way you like it. Repetitive tasks can be delegated to a function that can be stored and used in the future. It is even possible to write the results section of an article within RStudio, where the commands to insert all the statistics, tables and figures are in the document. RStudio will then generate a MS Word file ready to include in your manuscript. No more cutting and pasting figures or retyping tables to conform to journal guidelines. Of course, standard tools such as correlations, ANOVAs and regressions can be easily computed in R as well.
In this seminar, we assume that participants already know basic statistics through the general linear model (ANOVA and linear regression) and are familiar with at least one other statistics package such as SPSS, SAS or Stata.
The seminar will introduce the basics of how to work with R using examples and hands-on exercises. Many different types of statistical analyses will be illustrated and explained. Participants will also learn basic programming so they can harness the power of R to solve their own analytic problems.
Participants will learn how to use over a dozen different packages in R that provide advanced functionality and advanced statistical techniques.
This is a hands-on seminar with lots of exercises.