Let m be the number of independent variables,
ivs.' This function returns a<br> vector of length m which are the coefficients of a linear equation that best<br> predicts the dependent variable, dv,' in the least squares sense. It also
returns, as the second value, the sum of squared deviations of the data from the
fitted model, aka SSE, aka chi-square. The third value is the number of degrees
of freedom for the chi-square, if you want to test the fit.
This function returns an intermediate amount of information. Consider using the
sibling functions -minimal and -verbose if you want less or more information.