The relationship between variance estimation and adaptive quantization is investigated for memoryless Laplacian and Gaussian sources. Comparison of block average, exponential average, and maximum likelihood estimators in an adaptive quantization scheme indicates that estimator precision (variance) is more important than accuracy (bias) in minimizing distortion. Further, the block average and exponential average estimators are inconsistent when used in backward adaptive quantization.