## Function Linear-Regression-Brief-Summaries

(

**linear-regression-brief-summaries** < n > < x > < y > < x2 > < y2 > < xy > )

Calculates the main statistics of a linear regression: the slope and

intercept of the line, the coefficient of determination, also known as r-square,

the standard error of the slope, and the p-value for the regression. This

function differs from ` linear-regression-brief' 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.