Calculates almost every statistic of a linear regression: the slope and intercept of the line, the standard error on each, the correlation coefficient, the coefficient of determination, also known as r-square, and an ANOVA table as described in the manual. If you don't need all this information, consider using the ``-brief'' or ``-minimal'' functions, which do less computation. This function differs from `linear-regression-verbose' in that it takes summary variables: `x' and `y' are the sums of the independent variable and dependent variables, respectively; `x2' and `y2' are the sums of the squares of the independent variable and dependent variables, respectively; and `xy' is the sum of the products of the independent and dependent variables. You should first look at your data with a scatter plot to see if a linear model is plausible. See the manual for a fuller explanation of linear regression statistics.