Gaussian distribution is used when you have some observational data that boosts the probability of a certain event.
In case A, we already know that signal transmitted is say of amplitude 'A'. At receiving end we have a high probability of getting a signal of amplitude 'A' and the probability of signal with value being greater or lesser than a simply goes on decreasing(Signal distortion is caused by noise and has been practically proven that high amplitude noise is rare ie has low probability).
In case B we know particle can have any value in range -v to v. Hence we use uniform distribution. If we would have known that particle was fired with a velocity 'x', we would have considered gaussian distribution, cause we know particle still having velocity 'x' has high probability(It having a different value is also possible because of some interaction with other objects but that case will have low probability).
---------- Post added at 03:15 ---------- Previous post was at 03:14 ----------
Gaussian distribution is used when you have some observational data that boosts the probability of a certain event.
In case A, we already know that signal transmitted is say of amplitude 'A'. At receiving end we have a high probability of getting a signal of amplitude 'A' and the probability of signal with value being greater or lesser than a simply goes on decreasing(Signal distortion is caused by noise and has been practically proven that high amplitude noise is rare ie has low probability).
In case B we know particle can have any value in range -v to v. Hence we use uniform distribution. If we would have known that particle was fired with a velocity 'x', we would have considered gaussian distribution, cause we know particle still having velocity 'x' has high probability(It having a different value is also possible because of some interaction with other objects but that case will have low probability).