Home » Analytics » Interviews and Reviews: More R #rstats

Interviews and Reviews: More R #rstats

Software

R in the Cloud

Train in R

I got interviewed on moving on from Excel to R in Human Resources (HR) here at http://www.hrtecheurope.com/blog/?p=5345

“There is a lot of data out there and it’s stored in different formats. Spreadsheets have their uses but they’re limited in what they can do. The spreadsheet is bad when getting over 5000 or 10000 rows – it slows down. It’s just not designed for that. It was designed for much higher levels of interaction.

In the business world we really don’t need to know every row of data, we need to summarise it, we need to visualise it and put it into a powerpoint to show to colleagues or clients.”

And a more recent interview with my fellow IIML mate, and editor at Analytics India Magazine

http://analyticsindiamag.com/interview-ajay-ohri-author-r-for-business-analytics/

AIM: Which R packages do you use the most and which ones are your favorites?

AO: I use R Commander and Rattle a lot, and I use the dependent packages. I use car for regression, and forecast for time series, and many packages for specific graphs. I have not mastered ggplot though but I do use it sometimes. Overall I am waiting for Hadley Wickham to come up with an updated book to his ecosystem of packages as they are very formidable, completely comprehensive and easy to use in my opinion, so much I can get by the occasional copy and paste code.

 

A surprising review at R- Bloggers.com /Intelligent Trading

http://intelligenttradingtech.blogspot.in/2012/10/book-review-r-for-business-analytics.html

The good news is that many of the large companies do not view R as a threat, but as a beneficial tool to assist their own software capabilities.

After assisting and helping R users navigate through the dense forest of various GUI interface choices (in order to get R up and running), Mr. Ohri continues to handhold users through step by step approaches (with detailed screen captures) to run R from various simple to more advanced platforms (e.g. CLOUD, EC2) in order to gather, explore, and process data, with detailed illustrations on how to use R’s powerful graphing capabilities on the back-end.

Do you want to write a review too? You can visit the site here

http://www.springer.com/statistics/book/978-1-4614-4342-1

 


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