[R] understanding the output

[Ronaldo Reis Jr.]

Hi all,
I try to understand the output of the summary(model).
I make a simple model.

> summary(m1anova)

Call:
glm(formula = peso ~ gen)

Deviance Residuals: 
    Min       1Q   Median       3Q      Max  
-4.3114  -2.3788  -0.9167   2.1581   5.7856  

Coefficients:
            Estimate Std. Error t value Pr(>|t|)    
(Intercept)   4.8660     0.9808   4.961 0.000101 ***
gen2g         3.8504     1.3870   2.776 0.012459 *  
---
Signif. codes:  0 `***' 0.001 `**' 0.01 `*' 0.05 `.' 0.1 ` ' 1 

(Dispersion parameter for gaussian family taken to be 9.618818)

    Null deviance: 247.27  on 19  degrees of freedom
Residual deviance: 173.14  on 18  degrees of freedom
AIC: 105.92

Number of Fisher Scoring iterations: 2

I need the mean and se to make an plotbar (I know to make a plotbar)
The mean is easy to get.

> tapply(peso,gen,mean)
    1g     2g 
4.8660 8.7164 

The values is the same in estimate.
But the SE, when I try using tapply the SE is different os the SE of 
estimates. look

> tapply(peso,gen,sd)/sqrt(tapply(peso,gen,length))
       1g        2g 
0.8665567 1.0829789 

Why this difference? What SE I can use with mean???

When I use others errors that dont gaussian (poisson, binomial, etc), the mean 
is easy transformed (exp(x) for poisson) but how to use the SE? I can to use 
always the SE on the summary(model)? Or need transformation?

Thanks
Ronaldo
 
-- 
Hello, GORRY-O!!  I'm a GENIUS from HARVARD!!
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