Slowly-changing tonal signals are easy to approximate, while random noises are hard (see the examples below). The amplitude of quantization noise depends on the chosen bitrate and signal complexity.
The precision of this quantization depends on the selected bitrate, while quantization noise (a compression error: the difference between the original and the decoded signal) is spectrally shaped to be minimally audible - this is achieved by a psychoacoustic model. Lossy encoding can be viewed as a low-bit-depth quantization of a signal.
