<p>For the folks that are old enough, and who happen to be present in the US, the 2000 presidential elections with contoversial measurement errors on the split ballot created a strong splash of analyses and re-analyses. My adviser, Richard Smith, took a little longer than others, probably three or four months (I've seen at least two dozen analyses, and that was yet in the era when you had to write plain HTML rather than hit a "Post to blog" button on your iPhone), and he produced a very nicely rounded paper with good regression influence diagnostics, various ways of modeling the outlier, Poisson regressions with demographics of the counties, etc. -- see <a href="http://www.stat.unc.edu/faculty/rs/palmbeach.html" rel="nofollow">http://www.stat.unc.edu/faculty/rs/palmbeach.html</a>.</p>

<p>Somewhat similar uproar of grassroots statistical analyses was produced by the recent parliamentary election in Russia -- how many votes were actually fabricated? In normal elections, this would have been a plot with five Gaussian densities representing the votes cast for each of the participating parties: <a href="http://oude-rus.livejournal.com/542295.html" rel="nofollow">http://oude-rus.livejournal.com/542295.html</a> (the horizontal axis is the percent voted for a party, the vertical axis is the number of polling stations showing this percent, with a bin of 0.5%). I saw photos of protesters carrying this graph on rallies in Moscow and St. Petersburg.</p>

<p>So I think the opportunities present themselves where moderately complicated statistical analysis can create some visual aids that would aid the public in understanding a phenomenon. Great examples are provided in the joint journal of <a href="http://www.amstat.org" rel="nofollow">ASA</a> and <a href="http://www.rss.org.uk" rel="nofollow">RSS</a>, <a href="http://www.significancemagazine.org/view/index.html" rel="nofollow">Significance</a>. For instance, they had an <a href="http://www.significancemagazine.org/details/magazine/1324531/Fear-and-numbers-in-Fukushima.html" rel="nofollow">article</a> about how difficult it is to visualize the radiation exposures that may differ by 9 orders of magnitude in a meaningful way, without expecting people to understand the <code>log="xy"</code> option. This was in a special issue on Fukushima in the fall of 2011, about half a year after the disaster. I don't think you can excite the general public by saying, "Look, I've found a p-value of 0.0000001!" (or, for that matter, "I've found a Bayes factor of 1000000"). It has to be easily digestible, without the need to explaining why Bayes factors are better than p-values because they respect the likelihood principle, and yada-yada-yada. It has to be a picture telling a story that's worth a thousand words. Journalists have their <a href="http://www.poyi.org/" rel="nofollow">Picture of the Year</a> international contests; may be we could launch "Plot of the Year" contest aiming at explaining a social phenomenon with numbers and figures.</p>
