If you already know SAS, SPSS or Stata, you don’t need to spend time learning how to analyze data. You need a course that focuses on translating your knowledge into R. A course that facilitates switching from SAS, SPSS or STATA to R. That’s why DataCamp’s latest interactive course focuses on statisticians, data analysts, academic institutions, and companies that are switching (or planning to switch) from these commercial statistical software packages to the free and powerful language R.Like all DataCamp courses, this new course is self-paced, and offers you a great learning experience via a unique combination of challenging interactive exercises and to the point videos. It is given by Bob Muenchen, one of the leading instructors in the R community, and author of R for SAS and SPSS Users (Springer) and R for Stata Users (Springer).Supplementary to the course content, Bob offers free email support to all course subscribers. Furthermore, many online classes are yours for only 30 days, or for as long as you make an annual payment. This course is yours “forever”. So you can always go back to all the course materials when you need a refresher or some additional information.Check out the full course, or take the free preview.About an introduction to R for SAS, SPSS, and STATA usersR is a free and powerful software for data analysis and graphics that is rapidly disrupting the market for data analytical tools and software. It is flexible (no need to wait 6 months for updates), extremely comprehensive (over 6000 packages), cross-platform, and has a great community. However, if you come from another statistical software tool it can be a challenge to master the versatility of R. Enter DataCamp’s new interactive course Introduction to R for SAS, SPSS, and STATA Users. An ideal course for those switching from SAS, SPSS or STATA to R. This course:
- Introduces R jargon using language you’re familiar with.
- Points out the errors you’re most likely to make. For example, many R functions let you specify which data set to use in a way that looks identical to SAS, but which differs in a way that is likely to lead to perplexing error messages.
- Demonstrates add-on packages that produce output that is similar your current software’s. R’s built-in functions tend to provide surprisingly sparse output.
- Covers material to help you migrate to R, or to integrate the use of R into your current software.