Below are a few steps to perform one-way ANOVA and multiple comparisons in R.
Read data
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> data
sample m1 m2 m3
1 sample1 31226 944 2291
2 sample1 41729 1114 2687
3 sample2 22839 451 1501
4 sample2 44998 564 1786
5 sample3 22880 427 2518
6 sample3 19244 292 2130
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anova
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> fit1<-aov(m1~sample, data=data)
> summary(fit1)
Df Sum Sq Mean Sq F value Pr(>F)
sample 2 272983809 136491905 1.333 0.385
Residuals 3 307277393 102425798
> fit2<-aov(m2~sample, data=data); summary(fit2)
Df Sum Sq Mean Sq F value Pr(>F)
sample 2 494731 247366 24.78 0.0136 *
Residuals 3 29947 9982
+++
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
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Multiple comparison (TukeyHSD method)
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>TukeyHSD(fit2)
Tukey multiple comparisons of means
95% family-wise confidence level
Fit: aov(formula = m2 ~ sample, data = data)
$sample
diff lwr upr p adj
sample2-sample1 -521.5 -939.007 -103.993 0.0276687
sample3-sample1 -669.5 -1087.007 -251.993 0.0138238
sample3-sample2 -148.0 -565.507 269.507 0.4129937
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Plot
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> plot(m2~sample, data=data)
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