Statistical Graphics and more

As I know from past experience, statisticians usually don’t read what computer scientists do and vice versa. Thus I have good reason to assume that the two posts came up independently:

• Andrew Gelman’s Blog: What’s better than R for exploratory data plots?
• Robert Kosara’s EagerEyes: Where are the Visualization Tools?

Both are looking for good “out of the box” visualization tools, or a tool for exploratory data plots – I don’t see a difference here as long as you aim at data analysis with graphical tools.

Any further tools or thoughts?

I recently stumbled over the “Synoptic” project. It is a nice animated visualization of weather data – not particularly unique, but aesthetically well done.

I don’t have to argue about the lack of any generality regarding data analysis tasks here …

What caught my attention is the overall “staging” of the presentation. When you compare the “Synoptic” page with the (somewhat famous) demo movie of prefuse, you will pretty soon understand what I mean.

As a statistician – who grew up in an academic environment built up by math people – I can at least learn the marketing lessons here …

(Make sure to have your sound turned on, otherwise you will miss the point)

Here is what Andrew Gelman posted on his blog:

Like all nations who fight the global financial and economic crises, Germany has put a package over several hundred billion euros. One part of the package is the so called “Umweltprämie”, which is nothing else than a voucher over 2,500 euros for everybody who turns in his/her 9 or more years old car to be trashed and buys a new car.

Although we can assume the number of nine or more year old cars to be finite, there is a limit on the number of vouchers, which is set to 600,000. Now we come to the trivial plot. The simple pie chart shows the proportion of voucher given out so far.

I did start to record the numbers last week, and with a week worth of data the increase looks like this:

So far we seem to be still far away from the limit of 600,00. A simple linear regression yields this graph, and a results that tells us that the vouchers will be used up even before summer at May 31st:

The linear estimate is certainly not a very fancy prediction here … 

When we have something around three weeks of data, I will post the data and open up the round for the best prediction – stay tuned!

At www.politifact.com they put up the Obameter – the ultimate chart, which shows the progress of president Obama’s work.

Well, certainly not – or better not completely. It was the post at strangemaps which inspired me to check for something which I somehow always suspected, but never went after.

(don’t be fooled by the missmatch at the uncovered area in the south west; those guys elect the french president and not the german chancellor.) 

Everything started with the article in the NYT talking about R – and of course – did mention SAS. Andrew Gelman picked up the article and posted his take on the matter. Maybe it are sentences like Andrew’s “And it’s good to hear that SAS is in trouble” and Anne H. Milley, director of technology product marketing at SAS: “We have customers who build engines for aircraft. I am happy they are not using freeware when I get on a jet.”, which did stir the readers up.

Don’t miss this great 25min documentary on the London tube map. You find it at information aesthetics.
There is one central sentence by Milton Glaser I like most:
“…. All design basically is a strange combination of the intelligence and the intuition, where the intelligence only takes you so far and than your intuition has to reconcile some of the logic in some peculiar way. …”
This somehow gives us the limits how much we potentially can formalize or teach about (graph)-design.
Hard to believe that this map design is actually the prototype of all the subway maps around the world we are used to read in a unified manner today.

Attending a recent workshop on data visualization, the discussion after a presentation on a graphical display technique to visualize a particular type of data (sorry for not being more precise here, but the presenter would not like to be identified too easily) led to the quote of the speaker:

Matt pointed me to this nice report on Bill Gates trying to download one of “his” products.

Here is the e-mail, he sent to some of his staff.

Make sure not to miss the performance from Dave Ross of KIRO-AM/710 when reading this e-mail – very nice.

I wish this Bill Gates would have been more effective during his active career!

Again, in 2008 the most interesting thing for a statistician following the Tour de France is to look for means to detect possible doping cases. Right now we have the total results for the first 11 stages for all teams, and a simple boxplot of total time after stage 11 against team – ranked by the median time – looks like this: