As we believe you may know, we are having a webinar tomorrow (June 19^th, 2013) on Predictive Analytics. During this webinar, you are going to be introduced to R, learn how to build a predictive model and also how to carry insightful analysis through visualization.

As learning a new language can be a really difficult and painful process, we thought that it would be a valuable idea to share useful links for R resources with you. If you can spare some time to read some of these links, we believe that this first briefing will enable you to come with a better background to our webinar.

So, what do you say? Are you in for a reading and for reducing your learning curve?

Downloads

R : https://www.r-project.org/
Choose your nearest download location and click on the appropriate link
RStudio : http://www.rstudio.com/

Packages

RGoogleAnalytics :https://code.google.com/p/r-google-analytics/
Guide to getting started with RGoogleAnalytics :http://bit.ly/11kUgzI
Guide to getting started with ggplot2 :http://www.cookbook-r.com/Graphs/
Ggplot2 chart chooser :http://www.yaksis.com/posts/r-chart-chooser.html
Finding additional R packages for your domain : http://cran.r-project.org/web/views/
Additional Ideas for Predictive modelling :http://bit.ly/13XyCCK

Courses on R

Codeschool : http://tryr.codeschool.com/
2 minute short videos on R: http://www.twotorials.com/

Community

A Prezi tour of the R ecosystem :http://prezi.com/s1qrgfm9ko4i/the-r-ecosystem/
R news and tutorials from prominent R blogs : https://www.r-bloggers.com/
A search engine for R: http://www.rseek.org/

If you come across more resources, please ensure that you drop a comment below.

Would you like to understand the value of predictive analysis when applied on web analytics data to help improve your understanding relationship between different variables? We think you may like to watch our Webinar – How to perform predictive analysis on your web analytics tool data. Watch the Replay now!

Kushan Shah

Kushan is a Web Analyst at Tatvic. His interests lie in getting the maximum insights out of raw data using R and Python.

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