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Asked: 2026-05-13T22:15:20+00:00

The following script #!/usr/bin/Rscript –vanilla x <- c(4.5,6.4,7.2,6.7,8.8,7.8,9.6,7.0,5.9,6.8,5.7,5.2) fertilizer<- factor(c(‘A’,’A’,’A’,’A’,’B’,’B’,’B’,’B’,’C’,’C’,’C’,’C’)) crop <- factor(c(‘I’,’II’,’III’,’IV’,’I’,’II’,’III’,’IV’,’I’,’II’,’III’,’IV’)) av

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The following script 

#!/usr/bin/Rscript --vanilla
x <- c(4.5,6.4,7.2,6.7,8.8,7.8,9.6,7.0,5.9,6.8,5.7,5.2)
fertilizer<- factor(c('A','A','A','A','B','B','B','B','C','C','C','C'))
crop <- factor(c('I','II','III','IV','I','II','III','IV','I','II','III','IV'))
av <- aov(x~fertilizer*crop)
summary(av)

yields

                Df  Sum Sq Mean Sq
fertilizer       2 13.6800  6.8400
crop             3  2.8200  0.9400
fertilizer:crop  6  6.5800  1.0967

For other data, aov usually gives the F-statistic and associated p-value. What is wrong/special about this data that causes R to omit the juicy parts?

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1 Answer

  1. Editorial Team

    Should you using + instead of * in the formula?

    > summary(aov(x~fertilizer + crop))
            Df  Sum Sq Mean Sq F value  Pr(>F)  
fertilizer   2 13.6800  6.8400  6.2371 0.03426 *
crop         3  2.8200  0.9400  0.8571 0.51218  
Residuals    6  6.5800  1.0967                  
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
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