  Computational method for statistical measures of reliability, confidence, and
assurance are available for infinite population size. If the population size is
finite and small compared to the number of samples tested, these computational
methods need to be improved for a better representation of reality. This
article discusses how to compute reliability, confidence, and assurance
statistics for finite number of samples. Graphs and tables are provided as
examples and can be used for low number of test sample sizes. Two open-source
python libraries are provided for computing reliability, confidence, and
assurance with both infinite and finite number of samples.
