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I thank Max Bulsara and David Martin for the generous dissemination of their data. I also thank Ernesto Ramirez for reporting an error on the site. The simple method of 95% compliance limits is based on the assumption that the mean and standard deviation of the differences are constant, i.e. they do not depend on the size of the measurement. In our original work, we described the usual situation, where the standard deviation is proportional to the size, and described a method using a logarithmic transformation of the data. In our 1999 overall work (Bland and Altman 1999), we described a method for managing each relationship between the mean and SD of differences and the size of the measure. (That was Doug Altman`s idea, I can`t borrow.) that is statistically significant (P<0.001). If we multiply these coefficients with the square root of (pi more than 2), we get an equation to predict the standard deviation of the differences: Lin LI, Hedayat AS, Sinha B, et al. Statistical methods for assessing similarities: models, topics and tools. J Am Stat Assoc. 2002;97:257–70. Linear regression and pearson correlation coefficient are essential tests of accuracy and performance; However, both are influenced by dispersion. The Bland Altman differential diagram, also known as the tukey mean value difference graph, provides a graphical representation of the concordance between two trials.20 As with the t-test, Pearson correlation, and linear regression, the coupled test results are displayed in automated table columns.

This formula is used: σd being the standard deviation of the differences between the even values of X and Y. The lab professional generates t-test data by entering the forensic datasets side-by-side into columns in a table and applying an automated t-test formula. The program generates the number, mean and variance of each data set (sample; n1, n2; 1, 2; σ21, σ22) and the “degrees of freedom” (df) for the test: df = n1 + n2 – 2. . .