What programmers should know about Statistics

January 26, 2010

(This article was first published on Revolutions, and kindly contributed to R-bloggers)

Reader KW pointed me to this rant essay from Ruby on Rails enfant terrible Zed Shaw on what computer programmers don’t know about statistical analysis, but should. (Spoiler alert: a lot, apparently.) Perhaps surprisingly, building complex software systems often involves a lot of simulation, experimentation, and measurement for which statistical methods would be an asset. But according to Shaw, many programmers often have no idea how many iterations to run a test for, or why an average is often meaningless if you don’t also consider the variation, or how confounding factors can mess up an experiment. There’s actually some good statistical advice here, illustrated with examples from R

Zed Shaw: Programmers Need To Learn Statistics Or I Will Kill Them All

To leave a comment for the author, please follow the link and comment on their blog: Revolutions.

R-bloggers.com offers daily e-mail updates about R news and tutorials on topics such as: Data science, Big Data, R jobs, 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...

Tags: ,

Comments are closed.


Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)