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<br> variables: x' and y' are the sums of the independent variable and dependent<br> variables, respectively; x2' and y2' are the sums of the squares of the<br> 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.