Hi all,
a certain software has executed with problems occurring six times over a 33 day period:
Day 1, 10, 17, 18, 24 and 33. (Longest interval between problem days was 9 days)
On day 34 the software was updated with a version that was believed to fix the problem and the updated version has now run for 10 sequential days without the problem occurring.
What can be say about the probability that the problem has been fixed? What is the confidence level based on days passed without seeing the problem? How can this be calculated? Using which statistical model?
E.g. can one with say that the problem is fixed with x % probability after y days of trouble-free performance?
It can be assumed that no other parameters have changed that could cause the problem and that the occurrences are not dependent on each other.
Thanks!
In the real world, you can't let things stay broken just to get more data.
http://en.wikipedia.org/wiki/Poisson_distribution
There is a formula on the Wikipedia page for 95% confidence limit calculations.