11 December 2008
Amanda Cox from the NYT graphics department gave a fun talk yesterday about challenges she and her colleagues face.
One of the challenges she discussed is statistical uncertainty -- how to represent confidence intervals on polling results, for example, while not sacrificing too much clarity. Amanda provided a couple of examples where the team had done a pretty poor job of reporting the uncertainty behind the numbers; in some cases doing it properly would have made the graphic too confusing for the audience and in others there may have been a better way.
She also talked about "abstraction," by which I think she meant the issue of how to graphically represent multivariate data. She showed some multivariate graphics the NYT had produced (the history of oil price vs. demand, growth in the CPI by categorized component) that I thought were quite successful, although some in audience disagreed about the latter figure.
Amanda also showed the figure that I reproduced and discussed in an earlier post, in which I reported that the NYT graphics people think that the public can't understand scatterplots. Amanda disagrees with this (she said it annoys her how often people mention that point to her) and showed some scatterplots the NYT has produced. (She did say she thinks people understand scatterplots better when there is an upward slope to the data, which was interesting.)
The audience at the talk, much of which studies the media in some capacity and nearly all of which reads the NYT, seemed hungry for some analysis of the economics behind the paper's decision to invest so much in graphics. (Amanda said the paper spends $500,000 a month on the department.) Amanda wasn't really able to shed too much light on this, but said she felt very fortunate to be at a paper that lets her publish regression trees when, at many papers, the graphics team is four people who have their hands full producing "fun facts" sidebars and illustrations of car crash sites.