R-squared explanation needed.

[Stephen]

I am looking for further information on the R-squared
value when dealing with the trendline of a chart. A
description of what it is refering to and a break down of
the formula from Microsofy help (explanation of variables
and what they refer to.) If there are any mathematicians
out there please help.

 

[Tushar Mehta]

From XL help on LINEST:

In regression analysis, Microsoft Excel calculates for each point the
squared difference between the y-value estimated for that point and its
actual y-value. The sum of these squared differences is called the
residual sum of squares. Microsoft Excel then calculates the sum of the
squared differences between the actual y-values and the average of the
y-values, which is called the total sum of squares (regression sum of
squares + residual sum of squares). The smaller the residual sum of
squares is, compared with the total sum of squares, the larger the
value of the coefficient of determination, r2, which is an indicator of
how well the equation resulting from the regression analysis explains
the relationship among the variables.

--
Regards,

Tushar Mehta, MS MVP -- Excel
www.tushar-mehta.com
Excel, PowerPoint, and VBA add-ins, tutorials
Custom MS Office productivity solutions

 

[Mark Miller]

How the R-squared is calculated may not be as important as
how to interpret the R-squared number. Basically, R-
squared expresses how much of the actual change is
explained by the trend equation. 1.00 means all of the
change is explained. 0.75 means about 75 percent of the
change is explained. In other words, the closer R-squared
comes to 1.00, the better.

Hope this helps!