Frequency resolution: Once the signal in time domain becomes discrete, the freqeuncies can only be represented in the range of 0 to 2*pi.
now, let us say we have a signal x[n] which is represented by 10 samples and you take 10 point DFT on it, this will result in 10 frequency components called bins, with frequency resolution of (2*pi/10).
now, if the same signal is sampled at ten times the previous sampling rate so that you have 100 samples of the same signal for the same time duration. now if you take a 100 point DFT of this signal, you will get frequency bins spaced at (2*pi/100).
as you can see from the above example the frequency resolution has increased (meaning the spacing between adjacent frequency components has decreased) so that you can see even minor variations in the frequency characterstics of the signal x[n]..
i hope the concept of frequency resolution is clear now..