@Bumblefish

Which one is random?
(data sets are 100 numbers 1 to 6)

listA=[2,3,5,1,2,2,4,2,4,5,2,3,3,4,5,6,4,2,6,2,2,1,3,4,5,5,6,3,3,6,1,4,2,1,4,5,2,2,3,3,3,5,6,3,2,4,5,5,1,1,1,6,1,4,3,5,5,3,1,1,1,6,1,4,6,6,3,6,6,2,4,4,4,5,1,5,6,2,6,1,1,2,4,2,2,3,4,4,5,6,1,3,3,3,5,4,6,5,1,6]

listB=[4,2,5,6,3,5,3,1,3,4,2,3,4,3,4,5,5,1,3,3,2,1,1,6,1,3,2,2,2,6,1,5,6,3,6,3,2,3,2,4,6,1,1,6,3,2,4,1,6,1,3,1,5,6,2,3,3,5,1,6,4,5,2,5,1,1,5,3,6,2,3,3,6,5,2,3,3,1,6,3,2,3,2,1,6,6,4,4,6,2,4,5,4,5,3,4,6,5,3,2]

@futurebird
just to clarify what she means is as if from random unbiased 6 sided die rolls.

@Bumblefish

@futurebird
things I would check are first the frequency of each number... they should be somewhat uniform but not TOO close to equal as all exactly equal is unlikely... next I'd look at the length of repeat sequences and compare to expected values.

the actual definition of random sequences (Per Martin-Löf) is in terms of passing tests actually
@Bumblefish

@dlakelan @futurebird

The dictionaries in the Counter() object are the number of times each integer appears.

In [18]: Counter(listA)
Out[18]: Counter(
{2: 17, 3: 17, 5: 16, 1: 17, 4: 17, 6: 16}
)

In [19]: Counter(listB)
Out[19]: Counter(
{4: 12, 2: 17, 5: 14, 6: 17, 3: 24, 1: 16}
)

@alienghic
I'm on my phone at a volleyball game but what's the likelihood for each (probability of seeing that vector of counts given a multinomial distribution with 1/6 as probability for each value)

should be pretty easy in R or Julia or Python though offhand I would need to look at docs for any of them. Julia would be something like
using Distributions
pdf(Multinomial([1/6, 1/6,...], [17,17,17,17,16,16])
@futurebird