[R] Interpreting Multiple Linear Regression Summary
dwinsemius at comcast.net
Wed Nov 9 18:37:33 CET 2011
On Nov 9, 2011, at 12:04 PM, Rich Shepard wrote:
> I would appreciate pointers on what I should read to understand this
> summary(lm(TDS ~ Cond + Ca + Cl + Mg + Na + SO4))
I don't see a data= argument specified, so you are telling lm() that
your workspace has individual vectors by those names in the formula.
That is not what is implied by hte rest of your message.
> lm(formula = TDS ~ Cond + Ca + Cl + Mg + Na + SO4)
> ALL 1 residuals are 0: no residual degrees of freedom!
> Coefficients: (6 not defined because of singularities)
> Estimate Std. Error t value Pr(>|t|)
> (Intercept) 125 NA NA NA
> Cond NA NA NA NA
> Ca NA NA NA NA
> Cl NA NA NA NA
> Mg NA NA NA NA
> Na NA NA NA NA
> SO4 NA NA NA NA
> Residual standard error: NaN on 0 degrees of freedom
> (63 observations deleted due to missingness)
> When I look at the summary for the data frame used for this model I
> do not
> see an excessive number of missing values or indications why there
> are no
> residual degrees of freedom. The same model applied to 8 other data
> did not produce similar results.
> R-help at r-project.org mailing list
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
David Winsemius, MD
West Hartford, CT
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