Our school had a candy guessing contest for Hallowe’en. There were three Jars of Unusual Shape, and various sizes.
Jar 1: 108 Candies
Jar 2: 141 Candies
Jar 3: 259 Candies
The spirit of Francis Galton demanded that I look at the data. Candy guessing, like measuring temperature, is a classic case where averaging multiple readings from different sensors is expected to do very well. Was the crowd wise? Yes.
The unweighted average beat:
67% of guessers on Jar 1
78% of guessers on Jar 2
97% of guessers on Jar 3, and
97% of guessers overall
The median beat:
89% of guessers on Jar 1
83% of guessers on Jar 2
78% of guessers on Jar 3, and
97% of guessers overall
Only one person beat the unweighted average, and two others were close. There were 36 people who guessed all three jars (and one anonymous blogger who guessed only one jar and was excluded from the analysis). The top guesser had an overall error of 9%, while the unweighted average had an overall error of 11%. Two other guessers came close, with an average error of 12%. The worst guessers had overall error rates greater than 100%, with the worst being 193% too high.
The unweighted average was never the best on a single jar — though on Jar 3 it was only off by 1. (The guesser on Jar 3 was exactly correct.)
The measure I used was the overall Average Absolute %Error. The individual rankings change slightly If instead we use Absolute Average %Error, but the main result holds.
Have you ever wondered what will be the next ‘big thing’ in technology? What if you could garner collective wisdom from your peers – those who are interested in the same topics as you – with global reach?
Don’t miss two unique opportunities to learn more about how you can do this on SciCast (www.scicast.org), the largest known science and technology-focused crowdsourced forecasting site.
SciCast will be the featured topic in a Reddit Science AMA and an American Chemistry Society webinar this week! Don’t miss these opportunities to share your SciCast expertise and weigh in on the discussion. We also encourage you to share the information with your friends and colleagues.
SciCast Calls for Science, Technology Experts to Make Predictions
Largest sci-tech crowdsourcing forecast site in search of professionals and enthusiasts to predict future events
FAIRFAX, Va (June 19, 2014) – SciCast, a research project run by George Mason University, is the largest known science and technology-focused crowdsourced forecasting site. So what makes a crowdsourced prediction market more powerful? An even bigger crowd. SciCast is launching its first worldwide call for participants to join the existing 2,300 professionals and enthusiasts ranging from engineers to chemists, from agriculturists to IT specialists.