From: Matthew McKinney <mm.entomology_at_gmail.com>

Date: Tue, 15 Mar 2011 10:41:12 -0400

R-help_at_r-project.org mailing list

https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. Received on Tue 15 Mar 2011 - 15:51:05 GMT

Date: Tue, 15 Mar 2011 10:41:12 -0400

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I centered the dependent and predictor variables and then squared the
predictor to make a quadratic variable.

This left me with 3 variables:

MalesC

CellsC

CellsC2

I then used: >quadraticModel <- lm(MalesC ~ CellsC + CellsC2, data = dm)

This has given me R^2= 0.8821, F= 48.63, and p<0.001

I ran the exact same data in sigma plot and got identical results. My problem comes from the estimated coefficients I am getting in R when using >summary(quadraticModel). My coefficient estimates in sigma plot fit my data set well and agree with Microsoft excels estimates. The results from R appear to be the coefficients of a curve fitting the residuals. If I >plot(quadraticModel) it does not draw a curve fitting my data, but rather the residuals.

Thanks,

Matthew McKinney

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https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. Received on Tue 15 Mar 2011 - 15:51:05 GMT

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