i bought a pair of pants that seem a little too tight. if anyone knows anyone that's roughly my height and a little thinner than myself then i will give the aforementioned pair of pants to the aforementioned person.
-- Edited by The Libertarian Party at 12:48, 2008-05-05
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I'm Brittany's whore. what more do you want to know?
i bought a pair of pants, and then my dryer shrunk it, and now i can't walk in them without pinching my balls. You can have them if you want dave, should fit you.(unless my mom has other plans for them)
-- Edited by T Square Man at 13:43, 2008-05-05
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Words do not express the awesomeness of this signature.
In analytical chemistry and biostatistics, a Bland-Altman plot is a method of data plotting used in analysing the agreement between two different assays. It is identical to a Tukey mean-difference plot, which is what it is still known as in other fields, but was popularised in medical statistics by Bland and Altman.[1][2]
Bland and Altman make the point that any two methods that are designed to measure the same parameter (or property) will have a good correlation when a set of samples are chosen such that the property to be determined vary a lot between them. A high correlation for any two methods designed to measure the same property is thus in itself is just a sign that one has chosen a wide spread sample. A high correlation does not automatically imply that there is good agreement between the two methods.
Consider a set of n samples (for example, objects of unknown volume). Both assays (for example, different methods of volume measurement) are performed on each sample, resulting in 2n data points. Each of the n samples is then represented on the graph by assigning the mean of the two measurements as the abscissa (x-axis) value, and the difference between the two values as the ordinate (y-axis) value.
Hence, the Cartesian coordinates of a given sample S with values of S1 and S2 determined by the two assays is
One primary application of the Bland-Altman plot is to compare two clinical measurements that each provide some errors in their measure.[3] It can also be used to compare a new measurement technique or method with a gold standard even so the interest of the Bland-Altman plot is contested in this particular case because the error pertains to the sole new measure. See Analyse-it or MedCalc for software providing Bland-Altman plots.