The validation concepts in this essay only deal with the final binary result that can be applied to any qualitative test. However, the concepts can be applied to any other qualitative test.Verification and validation definitions are sometimes confusing in practice.In this sampling, the target population is the set of generic healthy individuals.The number of samples is a limitation to the statistical power of the study. If the number of samples does not affect the fixed percentage directly, its influence is critical to the 95% confidence interval (95% CI).Sometimes to obtain a “complete” sampling requires the use of commercial panels.Note that the infected individual sampling must only have samples from individuals.

Nominal quantities are related to binary results arising from the comparison of a numerical quantity results on an ordinal scale considering a certain decision point or “cutoff.” Sometimes in medical laboratories terminology, nominal **tests** are referred as qualitative - e.g., agglutination/positive/no-agglutination/negative in a slide, number of crosses of an observed certain reagent - and ordinal **tests** as semi-quantitative - e.g., positive result given that 4.12 is equal or higher than the “cutoff”=1.00.

ISO defines verification as the “confirmation, through the provision of objective evidence, which specified requirements had been fulfilled” (3.8.12 of [2]).

Validation is defined as the “confirmation, through the provision of objective evidence, that the requirements for a specific intended use or application have been fulfilled” (3.8.13 of [2]).

The worktable in this method is a 2x2 contingency table where positive and negative results from candidate test are measured “against” diagnostic accuracy criteria.

Table 1 shows a 2x2 contingency table and the equations to determine the diagnostic sensitivity and specificity.

Nominal quantities are related to binary results arising from the comparison of a numerical quantity results on an ordinal scale considering a certain decision point or “cutoff.” Sometimes in medical laboratories terminology, nominal **tests** are referred as qualitative - e.g., agglutination/positive/no-agglutination/negative in a slide, number of crosses of an observed certain reagent - and ordinal **tests** as semi-quantitative - e.g., positive result given that 4.12 is equal or higher than the “cutoff”=1.00.

ISO defines verification as the “confirmation, through the provision of objective evidence, which specified requirements had been fulfilled” (3.8.12 of [2]).

Validation is defined as the “confirmation, through the provision of objective evidence, that the requirements for a specific intended use or application have been fulfilled” (3.8.13 of [2]).

The worktable in this method is a 2x2 contingency table where positive and negative results from candidate test are measured “against” diagnostic accuracy criteria.

Table 1 shows a 2x2 contingency table and the equations to determine the diagnostic sensitivity and specificity.

This classification is referred as diagnostic sensitivity Se[%] when “the percentage (number fraction multiplied by 100) of subjects with the target condition (as determined by the diagnostic accuracy criteria) whose test values are positive”, and diagnostic specificity Sp[%] when “the percentage (number fraction multiplied by 100) of subjects without the target condition (as determined by the diagnostic accuracy criteria) whose test values are negative” (5.3 of [3]).