When we speak of LQAS and its origin, it goes way back. This is an ancient sampling approach which groomed with the passage of time – forming a convenient tactic for researchers to play with in their respective fields.
LQAS, also known as lot quality assurance sampling, is an approach introduced in 1920s. The approach was adopted by researchers to evaluate industrial processes and the products against certain pre-set standards.
As the name is self-explanatory, LQAS takes a small sample (usually 19) from a lot and tests its quality against specified indicators. These indicators (variables) may vary as per the requirement of the researchers or concerned industry/organization that wishes to adopt LQAS in its M&E (Monitoring and Evaluation) mechanism.
Sample size in LQAS is statistically determined via binomial probability.
As stated above, LQAS relies on considerably small sample size. Generally, a sample of 19 is recommended to check the quality of a lot.
Unlike other analytical tests and techniques used to analyze statistical data collected, analysis of information extracted from LQAS is quite simple. In any monitoring activity where sample extraction process is facilitated by LQAS, certain standard needs to be pre-set; it usually is a predetermined number (decision rule) to accept or reject a lot on the basis of its quality.
LQAS is not confined to industrial evaluation processes anymore. With the passage of time, different sectors and programs started adopting LQAS to facilitate their M&E process. As LQAS fame increased so did its implications.