Moderator: Tech Team
Mathematically, we would like to see if there is less than a 5% chance of achieving results that are at least as "bad" as these randomly. We use the Chi-squared test with 5 degrees of freedom (6 possible values of a die... subtract 1). So that p-value (critical value) is 11.07. If we get a Chi that is greater than 11.07, then we conclude that there is only a 5% chance of having rolls that are this far off from the norm.
Interesting ... what is the justification for 5%?Mathematically, we would like to see if there is less than a 5% chance of achieving results that are at least as "bad" as these randomly.
It is mostly custom. It comes from doing Normal analysis (z-tests), where the 5% chance indicates that something is more than 2 standard deviations away. Also, using 5% and 1% are actually endorsed by the U.S. Supreme Courthorizon wrote:Interesting ... what is the justification for 5%?Mathematically, we would like to see if there is less than a 5% chance of achieving results that are at least as "bad" as these randomly.
Some of the problems with this as mentioned above is that the chi-squared test doesn't measure how far off a single proportion is... for example it doesn't measure how far the number of sixes is from the norm, it measure the entire distribution at once. If the 6s were off in one test and the 2s were off in another, the chi-squared test could give you the same result, but it would not be further evidence that the distribution is flawed. It would be a better idea to pool the data and do the test over.horizon wrote:Thanks for the responce, subdork. OK, went out on the web and boned up on chi-squared test. Very informative, but leads me to another question.
Correct me if I am wrong - When using the chi-squared test to evaluate fair dice, we are saying that the observed variances can be attributed to "random fluctuations" when the chi-squared total is less than 11.07.
What if a signifcantly large number of the sample sets all have the same pattern of variance, for example the only significant portion of the chi-squared total comes from the same die face in each sample set. While these samples would be deemed fair according to the chi-squared test, surely they are not a statistically probable sample set and therefore can be classified as "un-random" using some other statistical analysis.
Thanks.
I'm already working on the individual game statsIdea: Maybe you should have a dice analyser for individual games inside the game, so you can see if you have been lucky of unlucky that game.
Good one, I'll make the modifications and post it, but I'll keep them separate, maybe someone likes this one better.Instead of having the ideal and actual stats next to each other, y dont u just have actual and in brackets the amount you are off.
It's because the <a> link which is pointing to the same page you're on. There is another onclick listener that opens the dice analyzer window. I can get rid of the <a> link but I need the onclick listener (you won't be able to right click and open in new tab).Anyone know how come when you right click open in new tab a page the same as the one you are on opens up and not the analyzer?
Interesting distribution, but they will start to even out when you get to 1000 dice.i know not many throws atm but it does seem very uneven even for 300 throws. ill come back here when its 1000 throws. nearly 40% 1 & 2's for attacker? im having real bad luck
Just clear your cookies and it should get back to 0.I have the dice analyzer installed, and have had for some time, but I'd like to zero the figures again, because I'm not sure they're accurate after a site upgrade some time back.
I tried uninstalling and reinstalling this dice analyzer, but the old figures are still there. Does anyone know what I can do to zero them?