[R] R vs. Excel (R-squared)
lance at quantumbioinc.com
Tue Jan 24 17:50:43 CET 2006
I found an inconsistency between the R-squared reported in Excel vs.
that in R, and I am wondering which (if any) may be correct and if
this is a known issue. While it certainly wouldn't surprise me if
Excel is just flat out wrong, I just want to make sure since the R-
squared reported in R seems surprisingly high. Please let me know if
this is the wrong list. Thanks!
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!
> # note: a is experimental and c is predicted
lm(formula = a ~ c - 1)
Min 1Q Median 3Q Max
-2987.6 -1126.6 -181.7 855.3 5602.8
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
system powerpc, darwin7.9.0
svn rev 36812
Thank you very much for your time!
Lance M. Westerhoff, Ph.D.
Email: lance at quantumbioinc.com
"Safety is not the most important thing. I know this sounds like heresy,
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The most important thing is to actually go." ~ James Cameron
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