Visualization of probabilistic forecasts

This week my research group dis­cussed Adrian Raftery’s recent paper on “Use and Com­mu­ni­ca­tion of Prob­a­bilis­tic Fore­casts” which pro­vides a fas­ci­nat­ing but brief sur­vey of some of his work on mod­el­ling and com­mu­ni­cat­ing uncer­tain futures. Coin­ci­den­tally, today I was also sent a copy of David Spiegelhalter’s paper on “Visu­al­iz­ing Uncer­tainty About the Future”. Both are well-​​worth reading.

It made me think about my own efforts to com­mu­ni­cate future uncer­tainty through graph­ics. Of course, for time series fore­casts I nor­mally show pre­dic­tion inter­vals. I pre­fer to use more than one inter­val at a time because it helps con­vey a lit­tle more infor­ma­tion. The default in the fore­cast pack­age for R is to show both an 80% and a 95% inter­val like this: Con­tinue reading →

A new candidate for worst figure

Today I read a paper that had been sub­mit­ted to the IJF which included the fol­low­ing figure


along with sev­eral sim­i­lar plots. (Click for a larger ver­sion.) I haven’t seen any­thing this bad for a long time. In fact, I think I would find it very dif­fi­cult to repro­duce using R, or even Excel (which is par­tic­u­larly adept at bad graphics).

A few years ago I pro­duced “Twenty rules for good graph­ics”. I think I need to add a cou­ple of addi­tional rules:

  • Rep­re­sent time changes using lines.
  • Never use fill pat­terns such as cross-​​hatching.

(My orig­i­nal rule #20 said Avoid pie charts.)

It would have been rel­a­tively sim­ple to show these data as six lines on a plot of GDP against time. That would have made it obvi­ous that the Euro­pean GDP was shrink­ing, the GDP of Asia/​Oceania was increas­ing, while other regions of the world were fairly sta­ble. At least I think that is what is hap­pen­ing, but it is very hard to tell from such graph­i­cal obfuscation.

Visit of Di Cook

Next week, Pro­fes­sor Di Cook from Iowa State Uni­ver­sity is vis­it­ing my research group at Monash Uni­ver­sity. Di is a world leader in data visu­al­iza­tion, and is espe­cially well-​​known for her work on inter­ac­tive graph­ics and the XGobi and GGobi soft­ware. See her book with Deb Swayne for details.

For those want­ing to hear her speak, read on. Con­tinue reading →

Reflections on UseR! 2013

This week I’ve been at the R Users con­fer­ence in Albacete, Spain. These con­fer­ences are a lit­tle unusual in that they are not really about research, unlike most con­fer­ences I attend. They pro­vide a place for peo­ple to dis­cuss and exchange ideas on how R can be used.

Here are some thoughts and high­lights of the con­fer­ence, in no par­tic­u­lar order. Con­tinue reading →

The Young Stats Communication Challenge

The Aus­tralian Young Sta­tis­ti­cians Con­fer­ence (Feb 2013) is orga­niz­ing a com­mu­ni­ca­tion com­pe­ti­tion. They invite all early-​​career sta­tis­ti­cians (study­ing, or within 5 years of grad­u­a­tion) to pro­duce a short (3−5 minute) video for the ABS YSC2013 Video Com­pe­ti­tion, or a sta­tic info­graphic for the ABS YSC2013 Info­graphic Competition.

Both com­pe­ti­tions have a 1st prize of $500, and 2nd prize of $250.

Entries close 16th Novem­ber, and win­ners will be noti­fied by mid-​​December.

Details avail­able at: ysc2013​.com/​p​r​o​g​r​a​m​/​c​o​m​p​e​t​i​t​ions/

I’m a speaker at the con­fer­ence, so hope­fully I will get to see some of the great entries!


Data visualization

For those who have not read the sem­i­nal works of Tufte and Cleve­land, please hang your heads in shame. To sal­vage some sense of self-​​worth, you can then head over to Solomon Messing’s blog where he is start­ing a series on data visu­al­iza­tion based on the prin­ci­ples devel­oped by Tufte and Cleve­land (with R examples).

The clas­sics are also worth read­ing, and remain rel­e­vant despite the 20 or 30 years that have elapsed since they appeared.

Data visualization videos

Prob­a­bly every­one has seen Hans Rosling’s famous TED talk by now. If not, here it is:

I recently came across a cou­ple of other excep­tional talks on data visualization:

Hans Rosling again: “Let my dataset change your mind­set”. If only all sta­tis­tics lec­tur­ers were this dynamic!

David McCan­d­less: “The beauty of data visu­al­iza­tion”. Not so excit­ing as Hans, but some great exam­ples.

And here’s an hour-​​length doc­u­men­tary hosted by Hans Rosling called “The Joy of Stats”.