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The Westgard rules are a set of statistical patterns, each being unlikely to occur by random variability, thereby raising a suspicion of faulty accuracy or precision of the measurement system. They are used for laboratory quality control , in "runs" consisting of measurements of multiple samples.
The Performance Test Standard PTC 19.1-2005 "Test Uncertainty", published by the American Society of Mechanical Engineers (ASME), discusses systematic and random errors in considerable detail. In fact, it conceptualizes its basic uncertainty categories in these terms.
If the users know the amount of the systematic error, they may decide to adjust for it manually rather than having the instrument expensively adjusted to eliminate the error: e.g. in the above example they might manually reduce all the values read by about 4.8%.
For example, an experimental uncertainty analysis of an undergraduate physics lab experiment in which a pendulum can estimate the value of the local gravitational acceleration constant g. The relevant equation [1] for an idealized simple pendulum is, approximately,
An example of a Levey–Jennings chart with upper and lower limits of one and two times the standard deviation. A Levey–Jennings chart is a graph that quality control data is plotted on to give a visual indication whether a laboratory test is working well. The distance from the mean is measured in standard deviations.
For example, alternate forms exist for several tests of general intelligence, and these tests are generally seen equivalent. [ 7 ] With the parallel test model it is possible to develop two forms of a test that are equivalent in the sense that a person's true score on form A would be identical to their true score on form B.
Since the announcement of Pons and Fleischmann in 1989, cold fusion has been considered to be an example of a pathological science. [15] Two panels convened by the US Department of Energy , one in 1989 and a second in 2004, did not recommend a dedicated federal program for cold fusion research. [ 16 ]
Any non-linear differentiable function, (,), of two variables, and , can be expanded as + +. If we take the variance on both sides and use the formula [11] for the variance of a linear combination of variables (+) = + + (,), then we obtain | | + | | +, where is the standard deviation of the function , is the standard deviation of , is the standard deviation of and = is the ...