[BioC] (Limma) LmFit and fit object

[Beatriz]

Hello to everybody!

I want to know everything about Linear Models.
I have read "limma: Linear Models for Microarray Data User's Guide" and 
"Bioinformatics and Computational Biology Solutions Using R and 
Bioconductor" but I'd like more "basic" information about this, because 
my statistical knowledge is... poor (I'm sorry).

I'm calculating the standard deviation and another statistical 
parameters with basic functions in R (like sd) because I don't know  the 
meaning of each fit "parameter" ($stdev.unscaled, $sigma, $lods...). I 
have read something about them in R help but I don't know how to 
interpret it

Any book or webpage?
could anybody explain it me?

thank you

BEATRIZ

***********************************************
 > fit2
An object of class "MArrayLM"
$coefficients
  1007_s_at     1053_at      117_at      121_at   1255_g_at
 0.06480576 -0.05789401  0.24983909  0.10716122  0.04500985
54670 more elements ...

$stdev.unscaled
1007_s_at   1053_at    117_at    121_at 1255_g_at
0.4472136 0.4472136 0.4472136 0.4472136 0.4472136
54670 more elements ...

$sigma
[1] 0.2250619 0.3603931 0.4365034 0.5544353 0.1156594
54670 more elements ...

$df.residual
[1] 4 4 4 4 4
54670 more elements ...

$cov.coefficients
     [,1]
[1,]  0.2

$pivot
[1] 1

$method
[1] "ls"

$design
        Vertical
55T_56T        1
20T_19T        1
40T_11T        1
26T_10T        1
25T_13T        1

$Amean
1007_s_at   1053_at    117_at    121_at 1255_g_at
 9.074874  5.801200  5.357923  7.232856  3.274542
54670 more elements ...

$df.prior
[1] 1.930101

$s2.prior
[1] 0.06249642

$var.prior
[1] 0.2326472

$proportion
[1] 0.01

$s2.post
[1] 0.05450763 0.10795045 0.14886179 0.22768891 0.02936421
54670 more elements ...

$t
 1007_s_at    1053_at     117_at     121_at  1255_g_at
 0.6206831 -0.3940092  1.4479507  0.5021711  0.5873317
54670 more elements ...

$p.value
1007_s_at   1053_at    117_at    121_at 1255_g_at
0.5578930 0.7073516 0.1983561 0.6336441 0.5786410
54670 more elements ...

$lods
[1] -4.865354 -4.933060 -4.456481 -4.904074 -4.876949
54670 more elements ...

$F
[1] 0.3852475 0.1552433 2.0965613 0.2521758 0.3449585
54670 more elements ...

$F.p.value
1007_s_at   1053_at    117_at    121_at 1255_g_at
0.5578930 0.7073516 0.1983561 0.6336441 0.5786410
54670 more rows ...