R’s role in the national response to the BP Oil Spill

August 12, 2010

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

In the early days of the Deepwater Horizon oil spill in the Gulf of Mexico, the rate of flow of oil from the spill was of great concern: estimating it accurately was key to coordinating the scale and scope of the response to the emergency. Unfortunately, estimates from independent sources varied widely, and BP’s own estimates varied widely over time. 

Antonio Possolo, Division Chief of Statistical Engineering at the National Institute of Science and Technology (NIST), was charged with making sense of these varied estimates to help the government coordinate the national response to the spill. As described in this video testimonial (starting at 2:20), Possolo was sitting in the company of the Secretaries of Energy and the Interior, when he broke out R on his laptop to run uncertainty analysis and harmonize the estimates from the various sources. In the video, Possolo is adamant in his confidence in his statistical analysis using the open-source R system. As he says to the crowd (including many of the developers of R), "The quality that you have built into R, through public, open examination, is the greatest strength and source of confidence I could have asked for." 

Blip.tv: useR talks, video #1

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.


Mango solutions

plotly webpage

dominolab webpage

Zero Inflated Models and Generalized Linear Mixed Models with R

Quantide: statistical consulting and training





CRC R books series

Six Sigma Online Training

Contact us if you wish to help support R-bloggers, and place your banner here.

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)