This research aims to present the importance of using statistical methods while establishing a quality
management system in the laboratory according to the requirements of the international standard ISO
17025:2005.
In addition the research describ
es how statistical analysis of the tests results works and includes a
practical study to evaluate the technical competence of the laboratory by using the most common
statistical methods (hypothesis testing) to study the results in a scientific way enables researchers to
identify weaknesses in the laboratory performance, and thus provides it with feedback and technical
advice helping to determine measurement problems and to check the Trueness of tests results.
Finally, the research provides recommendations and proposals such as a necessity of applying practical
methods for monitoring the performance of tests , making sure they meet quality requirements in terms of
trueness and precision , and working to remove the causes that affect the quality of performance during
all phases of testing, these proposals would – if they have been applied – support the laboratory to obtain
the certification in accordance with international standard ISO 17025:2005.
This paper deals with the problem of ability of separation for two simple
hypotheses. It is supposed that a family of probability
distributions on a measurable space, where i is an
unknown parameter, takes the value a sequence of
random variables
on this space which takes the values in the space,
are the two hypotheses about the right distribution for
the sequence.
According to the last basis, we present two theorems on the subject of this
paper. The first theorem deals with the criteria and the equivalent conditions
for the separability of the two hypotheses defined overhead. The second
theorem deals with one of these equivalent conditions when the random
sequence is a Markov sequence.
