[R] explalinig the output of my linear model analysis

[john56]

Hi,

I am new in statistics and i manage to make the linear model analysis but i
have some difficulties in explaining the results. Can someone help me
explalinig the output of my linear model analysis ? My data are with 2
variables habitat (e,s) and treatment (a,c,p) with multiple trials within.

Thank you in advance 

Call:
lm(formula = a$wild ~ a$habitat/a$treatment/a$trial)

Residuals:
    Min      1Q  Median      3Q     Max 
-58.905 -19.958  -5.774  16.693  88.890 

Coefficients:
                                Estimate Std. Error t value Pr(>|t|)    
(Intercept)                      55.4664     2.0332  27.281  < 2e-16 ***
a$habitats                      -11.9615     2.8753  -4.160 3.26e-05 ***
a$habitate:a$treatmentc           7.3581     2.8753   2.559  0.01054 *  
a$habitats:a$treatmentc          -4.9803     2.8753  -1.732  0.08335 .  
a$habitate:a$treatmentp         -13.9906     2.8753  -4.866 1.19e-06 ***
a$habitats:a$treatmentp         -16.1311     2.8753  -5.610 2.17e-08 ***
a$habitate:a$treatmenta:a$trial  -0.3204     0.3808  -0.841  0.40030    
a$habitats:a$treatmenta:a$trial  -0.1319     0.3808  -0.346  0.72905    
a$habitate:a$treatmentc:a$trial  -1.1250     0.3808  -2.954  0.00316 ** 
a$habitats:a$treatmentc:a$trial  -0.4236     0.3808  -1.112  0.26608    
a$habitate:a$treatmentp:a$trial  -0.3021     0.3808  -0.793  0.42775    
a$habitats:a$treatmentp:a$trial  -0.2873     0.3808  -0.754  0.45072    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 

Residual standard error: 26.8 on 3588 degrees of freedom
Multiple R-squared: 0.1383,     Adjusted R-squared: 0.1357 
F-statistic: 52.35 on 11 and 3588 DF,  p-value: < 2.2e-16 

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