R for Stata Users – August 2024
Event Phone: 1-610-715-0115
Upcoming Dates
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21AugR for Stata Users10:30 AM-3:00 PM
Cancellation Policy: If you cancel your registration at least two weeks before the course is scheduled to begin, you are entitled to a full refund (minus a processing fee of $50).
In the unlikely event that Statistical Horizons LLC must cancel a seminar, we will do our best to inform you as soon as possible of the cancellation. You would then have the option of receiving a full refund of the seminar fee or a credit towards another seminar. In no event shall Statistical Horizons LLC be liable for any incidental or consequential damages that you may incur because of the cancellation.
An 8-Hour Livestream Seminar Taught by Andrew Miles, Ph.D.
R is a free and open-source package for statistical analysis that is widely used in the social, health, physical, and computational sciences. While many excellent analysis packages exist, researchers gravitate to R because it is powerful, flexible, has excellent graphics capabilities, and is supported by a large and rapidly growing community of users.
This course is designed to help Stata users transition to R by understanding how to perform familiar data analysis tasks in R. Topics include data management and coding, exploratory data visualizations, and performing basic descriptive, bivariate, and multivariate analyses. Along the way, we will pay special attention to the differences between Stata and R such as terminology, code syntax, data handling, and default procedures.
This course is more than just a how-to guide for translating Stata code to R. While these kinds of translations can be helpful, the end goal is to help you become fluent in R. Thus, an important theme will be helping you understand the fundamentals of how R “thinks” so that you can begin to use R independently.
This course is thoroughly hands-on. You are encouraged to write code along with the instructor and to participate in the carefully designed exercises that will be interspersed throughout the seminar and assigned as “take-home” practice after the first class session. By the end of the course, you can expect to log more than six hours of guided practice coding in R.
Venue: Livestream Seminar