Andrew Gelman wrote today about some erroneous U.S. Governor approval ratings, noting that the ratings for Janet Napolitano sum to 108%.

In fact most of these ratings do not sum to 100%. I prepared a clean CSV file of the ratings, making use of `R`‘s `XML` library and the `readHTMLTable` function. The ratings data file is here `approval.csv`.

> approval <- read.csv("http://biostatmatt.com/csv/approval.csv")
> table( (approval$Excellent + approval$Good + approval$Fair + approval$Poor) - 100 )
-5 -4 -3 -2 -1 0 1 8
2 3 8 12 13 6 1 1

There is so much variability here, we could start to think about the sampling distribution, and the factors contributing to variability.

I don’t know much about this survey, or about survey conventions when reporting percentages. But I know my advisors wouldn’t have let me report percentages like this. Is it common to report percentages that sum to less that 100% when there is nonresponse? Or are these typos too? Also, where are the ratings for Hawaii, Idaho, Indiana, and Wyoming? (I knew learning the alphabetical state song in elementary school would be useful some day)

*Related*

To

**leave a comment** for the author, please follow the link and comment on their blog:

** BioStatMatt » R**.

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:** R, survey, Uncategorized