Function Linear-Regression-Verbose-Summaries

Part of:

package cl-mathstats
( linear-regression-verbose-summaries < n > < x > < y > < x2 > < y2 > < xy > )

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&#39; in that it takes summary<br> variables: x' and y&#39; are the sums of the independent variable and dependent<br> variables, respectively; x2' and y2&#39; 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