  Robert Machol's surprising result, that from a single observation it is
possible to have finite length confidence intervals for the parameters of
location-scale models, is re-produced and extended. Two previously unpublished
modifications are included. First, Herbert Robbins nonparametric confidence
interval is obtained. Second, I introduce a technique for obtaining confidence
intervals for the scale parameter of finite length in the logarithmic metric.
  Keywords: Theory/Foundations , Estimation, Prior Distributions,
Non-parametrics & Semi-parametrics Geometry of Inference, Confidence Intervals,
Location-Scale models
