I have two sets of data distribution between 0 to 100%. I was thinking of using the Bayes theorem of explaining the data distribution. More info on Bayes theorem:
http://en.wikipedia.org/wiki/Bayes%27_theorem
However, both of my data is not normally distributed.
1st dataset: 0-100% with midpoint of 16.66%. (Highest value obtained is 85% while lowest value 0%)
2nd dataset: 0-100% with midpoint of 16.66%. (Highest value 35% with lowest value 0%)
Both scales/data are independent of each other. However, I'm not sure which kind of probability theory to use. I was thinking Bayesian, but I'm not sure if Bayesian theory works with uneven data distribution. Can anyone tell me which theory should I be looking at? Can Bayesian work for uneven data distribution?
Thank you
http://en.wikipedia.org/wiki/Bayes%27_theorem
However, both of my data is not normally distributed.
1st dataset: 0-100% with midpoint of 16.66%. (Highest value obtained is 85% while lowest value 0%)
2nd dataset: 0-100% with midpoint of 16.66%. (Highest value 35% with lowest value 0%)
Both scales/data are independent of each other. However, I'm not sure which kind of probability theory to use. I was thinking Bayesian, but I'm not sure if Bayesian theory works with uneven data distribution. Can anyone tell me which theory should I be looking at? Can Bayesian work for uneven data distribution?
Thank you