K                                                        505 W GRAND BLVD 206 K                                                        CORONA CA 91720 2121 K                                                            19 DECEMBER 1992    Dear reader:  J One problem which recurs again and again in the engineering environment isJ centered around the so-called least-squares curve fit.  The coefficient ofJ linear correlation, r, is between -1 and 1.  When r is close to +1 or -1, I good correlation is indicated; a value of r close to 0 means little or no K correlation.  Some software outputs a more quantitative measure of goodness G of fit.  Two factors are used: (1) the number of points, N, and (2) the H value of the correlation coefficient, r.  The attached documentation andJ computer programs explain this quantative measure of fit and provide work- ing models.   I The graphical output of many commercial statistical packages does not in- H clude the construction of error bars.  This shortfall is closely tied toG the problem of goodness of fit.  If the line of best fit misses a large G proportion of the error bars or if it misses one or more significantly, J then there is little or no correlation.  This is true despite a value of rJ different from zero---if the number of data points, N, is small.  The doc-I ument provides a vehicle for the correct graphical display of statistical  data.   J 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