Originally Posted by
danc_ie Greetings all,
I am testing a modification to an algorithm to see if significant
performance gains can be observed when compared with the
original algorithm.
I have performed 30 trials of each on a benchmark problem and I
have two sets of performance results to compare (higher values
being better).
Using a 95% confidence interval, I can observe (graphically) that
there is no overlap between the error-bars, the modified method
shows mean performance window "above" the original method.
Using a paired t-test, I obtain a P-value less than 0.05.
My question is -- are these two methods functionally equivalent?
In a paper I'm writing I am using the confidence intervals to claim
a statistically significant performance improvement.
Is this sufficient or am I potentially leaving myself open to criticism
by more experienced statisticians than myself?
Any comments would be most welcome. Many thanks,
dan