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MIL-STD-105 D Quick reference Table, TABLE I and TABLE IIA. MIL-STD-105 was a United States defense standard that provided procedures and tables for sampling by attributes based on Walter A. Shewhart, Harry Romig, and Harold F. Dodge sampling inspection theories and mathematical formulas. Widely adopted outside of military procurement applications.
In general, acceptance sampling is employed when one or several of the following hold: [2] testing is destructive; the cost of 100% inspection is very high; and; 100% inspection takes too long. A wide variety of acceptance sampling plans is available. For example, multiple sampling plans use more than two samples to reach a conclusion.
A variables sampling plan can be designed so that the OC curve passes through two points (AQL,) and (LQL,). AQL and LQL are the Acceptable quality limit and the limiting quality level respectively. α {\displaystyle \alpha } and β {\displaystyle \beta } are the producer and consumer's risks.
The table shown on the right can be used in a two-sample t-test to estimate the sample sizes of an experimental group and a control group that are of equal size, that is, the total number of individuals in the trial is twice that of the number given, and the desired significance level is 0.05. [4]
Lot quality assurance sampling (LQAS) is a random sampling methodology, originally developed in the 1920s [1] as a method of quality control in industrial production. Compared to similar sampling techniques like stratified and cluster sampling , LQAS provides less information but often requires substantially smaller sample sizes.
The acceptable quality limit (AQL) is the worst tolerable process average (mean) in percentage or ratio that is still considered acceptable; that is, it is at an acceptable quality level. [1] Closely related terms are the rejectable quality limit and rejectable quality level (RQL).
Fisher's exact test (also Fisher-Irwin test) is a statistical significance test used in the analysis of contingency tables. [1] [2] [3] Although in practice it is employed when sample sizes are small, it is valid for all sample sizes.
Let H be a Hadamard matrix of size s, and choose one row per half-sample. (It doesn't matter which rows; the important fact is that all the rows of H are orthogonal.) Now, for each half-sample, choose which unit to take from each stratum according to the sign of the corresponding entry in H : that is, for half-sample h , we choose the first ...