Gauss error curve

The function e a< x z ), is called a Gauss error curve, having been used by Gauss to describe distribution functions similar to our /( ) in the theory of errors. It equals unity when x = x0, and falls off on both sides of this point symmetrically, being reduced to 1 /e when... 

Normal Law Normal Law of Error Normal or Gaussian Distribution Law Gauss Error Curve Probability Curve... 

Note that Laplace (not Gauss) first derived the equation for the Gaussian (normal) error curves, which need not be normal in the sense that they normally apply to errors encountered in practice (text above). 

This is based on the arbitrary assumption, discussed further below, that the distribution of combining energies (which are proportional to log K) in a normal antibody population obeys a Gauss error function. Ko, the average K value, is that represented by the peak of the distribution curve. 

One approach is to assume that there is a continuous distribution of antibody populations with respect to the free energy of interaction with hapten, or with respect to In K, which is proportional to AG . One can assume a Gauss error distribution (74), or the Sips relationship (75,76), which closely approximates a Gaussian type of distribution curve. On the basis of the latter assumption one obtains the following relationship ... 

The normal distribution and the statistical tools linked with it are the most important statistical tools in analytical chemistry. The normal distribution was first studied by the German mathematician Carl Friedrich Gauss as a curve for the distributions of errors. 

The normal distribution was first introduced by de Moivre, who approximated binomial distributions for large n (Figure D.3). His work was extended by Laplace, who used the normal distribution in the error analysis in experiments conducted. Legendre came up with the method of least squares. Gauss, by 1809, justified the normal distribution for experimental errors. The name bell curve was coined by Gallon and Lexis. 

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