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Accuracy is also used as a statistical measure of how well a binary classification test correctly identifies or excludes a condition. That is, the accuracy is the proportion of correct predictions (both true positives and true negatives) among the total number of cases examined. [10] As such, it compares estimates of pre- and post-test probability.
The repeatability coefficient is a precision measure which represents the value below which the absolute difference between two repeated test results may be expected to lie with a probability of 95%. [citation needed] The standard deviation under repeatability conditions is part of precision and accuracy. [citation needed]
Reproducibility, closely related to replicability and repeatability, is a major principle underpinning the scientific method.For the findings of a study to be reproducible means that results obtained by an experiment or an observational study or in a statistical analysis of a data set should be achieved again with a high degree of reliability when the study is replicated.
ANOVA gauge repeatability and reproducibility is a measurement systems analysis technique that uses an analysis of variance (ANOVA) random effects model to assess a measurement system. The evaluation of a measurement system is not limited to gauge but to all types of measuring instruments , test methods , and other measurement systems.
In engineering, science, and statistics, replication is the process of repeating a study or experiment under the same or similar conditions to support the original claim, which is crucial to confirm the accuracy of results as well as for identifying and correcting the flaws in the original experiment. [1]
Quantification of measurement uncertainty, including the accuracy, precision including repeatability and reproducibility, the stability and linearity of these quantities over time and across the intended range of use of the measurement process. Development of improvement plans, when needed.
In practice, testing measures are never perfectly consistent. Theories of test reliability have been developed to estimate the effects of inconsistency on the accuracy of measurement. The basic starting point for almost all theories of test reliability is the idea that test scores reflect the influence of two sorts of factors: [7] 1.
In a classification task, the precision for a class is the number of true positives (i.e. the number of items correctly labelled as belonging to the positive class) divided by the total number of elements labelled as belonging to the positive class (i.e. the sum of true positives and false positives, which are items incorrectly labelled as belonging to the class).