# [R] R vs. Excel (R-squared)

From: Lance Westerhoff <lance_at_quantumbioinc.com>
Date: Wed 25 Jan 2006 - 03:50:43 EST

To begin, I have a set of data points in which the y is the experimental number and x is the predicted value. The Excel- generated graph (complete with R^2 and trend line) is provided at this link if you want to take a look:

As you can see, the R-squared that is reported by Excel is -0.1005. Now when I bring the same data into R, I get an R-square of +0.9331 (see below). Being that I am new to R and semi-new to stats, is there a difference between "multiple R-squared" and R-squared that perhaps I am simply interpreting this wrong, or is this a known inconsistency between the two applications? If so, which is correct? Any insight would be greatly appreciated!

Call:
lm(formula = a ~ c - 1)

Residuals:

Min 1Q Median 3Q Max -2987.6 -1126.6 -181.7 855.3 5602.8

Coefficients:

Estimate Std. Error t value Pr(>|t|)
c 0.99999 0.01402 71.33 <2e-16 ***

```---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 1423 on 365 degrees of freedom
Multiple R-Squared: 0.9331,	Adjusted R-squared: 0.9329
F-statistic:  5088 on 1 and 365 DF,  p-value: < 2.2e-16

> version

_
platform powerpc-apple-darwin7.9.0
arch     powerpc
os       darwin7.9.0
system   powerpc, darwin7.9.0
status
major    2
minor    2.1
year     2005
month    12
day      20
svn rev  36812
language R

======================

Thank you very much for your time!

-Lance
____________________
Lance M. Westerhoff, Ph.D.
General Manager
QuantumBio Inc.

WWW:    http://www.quantumbioinc.com
Email:    lance@quantumbioinc.com

"Safety is not the most important thing. I know this sounds like heresy,
but it is a truth that must be embraced in order to do exploration.
The most important thing is to actually go."  ~ James Cameron

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Received on Wed Jan 25 04:00:00 2006

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