505 W GRAND BLVD 206 CORONA CA 91720 2121 19 DECEMBER 1992 Dear reader: One problem which recurs again and again in the engineering environment is centered around the so-called least-squares curve fit. The coefficient of linear correlation, r, is between -1 and 1. When r is close to +1 or -1, good correlation is indicated; a value of r close to 0 means little or no correlation. Some software outputs a more quantitative measure of goodness of fit. Two factors are used: (1) the number of points, N, and (2) the value of the correlation coefficient, r. The attached documentation and computer programs explain this quantative measure of fit and provide work- ing models. The graphical output of many commercial statistical packages does not in- clude the construction of error bars. This shortfall is closely tied to the problem of goodness of fit. If the line of best fit misses a large proportion of the error bars or if it misses one or more significantly, then there is little or no correlation. This is true despite a value of r different from zero---if the number of data points, N, is small. The doc- ument provides a vehicle for the correct graphical display of statistical data. It is hoped that the user of this document and the computer programs will be spared from the need to constantly "re-invent the wheel." Harry A. Watson, Jr. (909) 737-3958
maad – Mathematical Approximations and Documentation
A document describing the parameterisation of least-squares curve fitting, and showing how (using PiCTeX) to display error bars.
|License||Public Domain Software|
|Maintainer||Harry A. Watson, Jr|