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
explain 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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