The statistics software signal

January 5, 2013
By

(This article was first published on Statistical Modeling, Causal Inference, and Social Science » R, and kindly contributed to R-bloggers)

Tyler Cowen links to a post by Sean Taylor, who writes the following about users of R:

You are willing to invest in learning something difficult. You do not care about aesthetics, only availability of packages and getting results quickly.

To me, R is easy and Sas is difficult. I once worked with some students who were running Sas and the output was unreadable! Pages and pages of numbers that made no sense. When it comes to ease or difficulty of use, I think it depends on what you’re used to! And I really don’t understand the bit about aesthetics. What about this? One reason I use R is to make pretty graphs. That said, if I’d never learned R, I’d just be making pretty graphs in Fortran or whatever. My guess is, the way I program, R is actually hindering rather than helping my ability to make attractive graphs. Half the time I’m scrambling around, writing custom code to get around R’s defaults.

The post The statistics software signal appeared first on Statistical Modeling, Causal Inference, and Social Science.

To leave a comment for the author, please follow the link and comment on his blog: Statistical Modeling, Causal Inference, and Social Science » R.

R-bloggers.com offers daily e-mail updates about R news and tutorials on topics such as: visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git, hadoop, Web Scraping) statistics (regression, PCA, time series, trading) and more...



If you got this far, why not subscribe for updates from the site? Choose your flavor: e-mail, twitter, RSS, or facebook...

Comments are closed.