Statistics for Data Science
Today’s lecture for Big Data Analytics included statistical tools for data analysis.
My Data Pro Tumble blog includes several listings and resources concerning statistics <http://mountainsol.tumblr.com/tagged/statistics>.
From the perspective of an information scientist, statistical analysis software is not just the computation done, but preservation of both the input, output, and processing.
One of the more popular statistical software packages is R, which actually does a lot more than work with statistics (as one of my recent tweets showed):
There’s a short introduction to R which explains:
R is a tool for statistics and data modeling. The R programming language is elegant, versatile, and has a highly expressive syntax designed around working with data. R is more than that, though — it also includes extremely powerful graphics capabilities. If you want to easily manipulate your data and present it in compelling ways, R is the tool for you.
It’s also possible to run R from the terminal in Mac OS X, but a nice interface for using R is R Studio <https://www.rstudio.com/>.
Other useful links: