If there's one thing Shapeways is suited to, it's speciality dice.
There's a whole section for them, and they often appear on the front page.
So when I started to design my own I was slightly surprised to find no special interest thread. I just don't know why not, because I'm sure there are things we could productively talk about.
For myself, I'm particularly concerned about the fairness of the dice. How are people testing for bias? When print orientation matters, do you find that they get positioned appropriately?
I will try to start and get the discussion rolling, with what I do for bias testing.
Basically the process I have at the moment is to buy a single die, and roll it
100*n times, where
n is the number of sides.
I try to roll it in a manner which will highlight any issues - for example a roller should roll and come to a stop without hitting anything. And I try to define miss-rolls strictly and declare them without looking at the number (for metal dice the sound is a good indicator).
Then a chi-square test indicates whether there is any evidence that the die is not fair, and I add a comment to that effect to the listing.
But there are some things I don't like about this:
[list type=square]
[*] Only a single instance of the design is tested.
[*] Being impartial on the rolls is really hard. I think I'm managing, but who would trust that?
[*] The test doesn't have as much power as I'd like.
[*] Sometimes (one time in 20) the test will reject even a perfectly fair die.
[*] I'm not sure my report actually makes sense to people[/list]
Overall I'm a bit concerned that reporting the data may put customers off rather than reassure them.
Obviously I could buy more dice and test them for many more throws, but even what I'm doing is a job of work, and that wouldn't solve the other issues.
And I should also say that I appreciate that this is also a deal more work for a D20 than a D6.
Links:
chi-square test (basic description with probability table)
More on die fairness testing (Useful introduction, and also has something on a test with more power, suitable for larger dice.)
On the power of the chi-square test (How discrimination relates to number of trials, and how a negative result doesn't prove fairness.)