[R] Help needed in interpreting linear models

[Petr PIKAL]

I forgot to post it to r help.
Petr

Hi

> 
> Hi Petr,
> 
> thanks for your answer.
> 
> First of all it's not homework I am a student and need to analyse cancer
> data using linear models.
> I looked into that topic since a week now and still struggling in
> interpreting some of the R output that is why
> I was asking for help here.
> 
> I don't quite understand your answer because the 180/190 values belong 
to
> height and not to weight. What do you want to 
> show with plot(scores,weight). What I can see from the plot is that 
there is
> a correlation between the two variables and 
> therefore weight "explains" scores.

Yes, but as far as I remember (I do not keep mails so now I can not see 
the data you posted - Nabble is not available for me) I said that the 
height value 190 (which was unique, all others were 180 if I remember 
correctly) is pointing to scores/weight pair which is slightly out from 
the simple linear model

lm(scores~weight)

so it is kind of an outlier from the model. Therefore adding the variable 
(height) to the model improves it and therefore the height variable in the 
second model is slightly significant as you found from anova.

You can also inspect your models by

plot(predict(fit), y.variable)
abline(0,1)

The better is the model the more close are the points to 0,1 line. Of 
course you can use some more formal evaluation (residuals, hatvalues...) 
and you can find appropriate literature e.g. at CRAN web. Those two are my 
favourites, however there are plenty other sources.

Using R for Data Analysis and Graphics - Introduction, Examples and 
Commentary” by John Maindonald (PDF, data sets and scripts are available 
at JM's homepage). 
“Practical Regression and Anova using R” by Julian Faraway (PDF, data sets 
and scripts are available at the book homepage). 

Regards
Petr

> 
> Regards
> 
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