Introduction to R and R Commander for a variety of academic-research statistical analyses

[Geoffrey Hubona-2]

(my apologies if you inadvertently receive this message more than once)

 

The Center for Corporate Education (CCE), funded by the School of Business Foundation at Virginia Commonwealth University (VCU), is offering a winter-term, non-credit, continuing education, live, interactive, synchronous online class introducing the use of R for a variety of academic-research statistical analyses, including: inference; ANOVA; simple, multiple and logistic regression; analyzing longitudinal data; and simultaneous inference and multiple comparisons. The limited time, early sign-up cost for the 14-hour, 5 week course is $195 (student); $250 (faculty); and $295 (practitioner). This course will be popular so please do not wait if you are interested. If you sign up now and your plans change, we will work to reschedule you (or refund your deposit, less $25, if that is what you prefer).

 

The informational (and registration) site for the AM version (in the Eastern US) is here: https://www.regonline.com/R-vcu-feb-AM

 

The informational (and registration) site for the PM version (in the Eastern US) is here: https://www.regonline.com/R-vcu-feb-PM

 

The R Project for Statistical Computing provides a comprehensive environment for statistical analysis and graphics and is unrivaled in the availability of new, cutting-edge applications. R is a very powerful system for statistical computations and graphics, and runs on Windows, UNIX and Mac computers. It may be described as a combination of a statistics package and a programming language. It is freely available for download from http://www.r-project.org/ .

 

We designed this course specifically for researchers and statistical workers who want to learn a powerful new software platform for conducting a variety of essential academic research statistical analyses, including: (1) the statistical graphical displays available in R; (2) simple inference; (3) analysis of variance; (4) simple and multiple regression; (5) logistic regression; (6) analyzing longitudinal data; and (7) simultaneous inference and multiple comparisons.

 

The number of R users was estimated at 2,000,000 in 2009 (http://bits.blogs.nytimes.com/2009/01/08/r-you-ready-for-r/). We like to think of R as ‘open source SAS.’ But R is free and widely supported. It you crunch numbers for a living and you have not used R, now is a good time to start.

This course illustrates how to use R for common, research-oriented statistical analyses using generic data provided with the HSAUR2 data package which is available with or without the (optional) textbook. We will also use R Commander, the freely-available, menu-driven, statistics-oriented visual interface to R to illustrate how to utilize the various statistical functions.

 

This live, interactive, synchronous online course (which has both an AM and a PM version to reach all time zones) is conducted in four separate, weekly 3-hour sessions. There is also a pre-class session  to ensure that everyone has installed R and R Commander without problems. All classes are recorded and provided to participants so, if you miss a class, you will have the recording. Also, you may switch from AM to PM (or vice versa) as space allows (although you initially sign up for one or the other). There is also information available at http://www.pls-seminars.com.

 

Don’t wait ! Join the ‘R’ revolution ! You will be glad that you did ! And get an R course completion certificate in the process !

 

Feel free to email me with any questions/issues/etc.

 

Geoff Hubona