I was playing a game with my son, and it seemed that we rolled two or five about half the time. He was wondering if the die was weighted.
So I re-rolled it a bunch of times and jotted down the results:
1: 4 times
2: 12 times
3: 13 times
4: 4 times
5: 13 times
6: 8 times
I realise that this is a small sample (only 54 datapoints), but to my very untrained eye, the 1 and 4 seem very low. I was wondering how I would go about determining the probability that the die is fair. I was expecting about 9 each. I did a ChiTest in excel, which I am not sure how to calculate manually and got 0.069
Does this mean that there's a 6.9% chance that the die is unweighted, and therefore a 93.1% chance it's weighted, or have I misinterpreted the results entirely?
This is not the right interpretation of the $0.069$ number. Indeed, this wrong interpretation is extremely common, and people from doctors to judges to scientists to policy makers routinely get this wrong (and go on to make poor decisions as a result).
The $0.069$ number means this: if your die is fair, then the probability of getting a result at least as extreme as the one you observed is $0.069$. In other words, if you do sets of 54 trials over and over again, you'll see distribution as extreme or more in 6.9% of the trials.
You can use this informtaion however you want to make deductions about whether the die is fair or unfair. However, it makes no sense to talk about "the probability that the die is fair" unless we have an underlying space of all possible events as reference (all dice in the world, for example, or all ways of manufacturing dice). The result from a chi-square test simply does not provide that type of information.