In many cases quantitative information relies on statistical interpretations to highlight trends in what seem to be a bunch of abstract numbers. Most people will probably encounter statistics when faced with election polls or census data. In the run-up to the US election statisticians for both the democrats and republicans where most probably vetting the odds of winning the election by taking into account a whole bunch of 'voting' minorities; the African-American vote, the womens vote, the latino vote, the youth vote etc... They were probably asking questions like: what is the likelyhood of Obama wining the state Ohio if he gets 86% of the womens vote in, let's say, the state of Colorado? Or, what is the likely-hood that Latino women will vote for John McCain and Sarah Palin? Latino women, obviously falling into the categories of both women voters an Latino voters.
Statistics is daunting and getting a grasp of it as quantitative scientist is, (un)fortunately compulsory - depending on whether you are the graduate student who is tearing his hair out in frustration or the public who rely on politicians taking (or not) the advice of the scientific community (see the preCOP9 conference in 2008 where scientists strived to make some recommendations to the parties taking part in the meeting).
Although statistics relies on mathematical equations to define the odds of an event happening or a relationship existing, they also depend on graphs and figures to display statistical trends succinctly. Perhaps more importantly, because we are a species largely relying on our eyesight, it is important for our understanding to display these results visually. And here lies the problem. In many cases graphs and figures are, to the untrained eye, illegible. The British government and many Universities (see this for one of Manchester's attempts) are trying to spur scientists to take a more active role in engaging the public and making science more accessible to wider audiences. When speaking to my friend Paul (Finn) about my idea for a book about my work in Ecuador I was struck by his interest in data and visually representing data. Paul is a graphic designer who loves fronts (listen to this if you want to laugh at him expressing his love for fonts to the BBC's Saturday Live). Talking to him made me realize that there is not a lot of stuff out there, specifically aiming to look at data and focusing on it's visual representation, particularly in the natural sciences. The NY Times does very well at exploring new media and data and I have selected three pieces which I think are very good.