I've got a data-set which I assume is uniformly distributed. Say I've got
N=20000 samples and a suspected
p=0.25. This means that I would expect each option to show up roughly
How do I calculate the following interval
[5000 - x, 5000 + x] such that I can say with a certain confidence that the data-set is probably NOT uniformly distributed since the number of times an option shows up falls outside of the interval?
EDIT ABCDBCDADBCDA, BDCAADBCDADBA, ADCDBDACDBDAD, CDBDACDBDACDA, That's some sample data. A sample is one cookie string! Now I want for each position in that cookie string determine if a character there is too rare or too common at that position. So I count, for all samples, the number of A's on positon 0, the number of B's, C's and D's. Suppose I get a count of 5 A's on position 0 and I would expect a count of roughly 50 A's then the character A is too rare at position 0. That's what I want to do for each character position.