Gaussian filter as a low pass filter Can anyone explain me how is a Gaussian filter a low pass filter? It may be a simple thing but I just can't seem to wrap my head around it. Also while applying a low pass filter for bandlimiting (to prevent aliasing), which of the following two is better:
(a) Applying Gaussian filter to the signal.
(b) Applying Box filter in the frequency domain and then 
      using IFT on the resultant.
I think option (a) is better because we just convolve the signal with a Gaussian while in option (b) we first need to get the FT, then apply the filter and then convert back using IFT. But what about the quality of the resultant signal?

I'm still a newbie so answers with less jargon will be appreciated.
it's because all of the filter coefficients (which is the impulse response $h[n]$) are positive and there is no "ringing" in the impulse response.

so, assuming the impulse response is scaled so that all of the $h[n]$ add to 1, the output of the gaussian filter will be a weighted average of the input.  averaging is a process that removes high-frequency variation.  so what is left are the low frequencies, like DC.  that's what a low-pass filter does.