  Bucklew and Wise (1982) showed that the quantization dimension of an
absolutely continuous probability measure on a given Euclidean space is
constant and equals the Euclidean dimension of the space, and the quantization
coefficient exists as a finite positive number. By giving different examples,
in this paper, we have shown that the quantization coefficients for absolutely
continuous probability measures defined on the same Euclidean space can be
different. We have taken uniform distribution as a prototype of an absolutely
continuous probability measure. In addition, we have also calculated the
conditional optimal sets of $n$-points and the $n$th conditional quantization
errors for the uniform distributions in constrained and unconstrained
scenarios.
