ANOVA

x<-data.frame(t1=c(2.5,2.2,2.1,2.3),
              t2=c(1.8,1.5,1.4,1.5),
              t3=c(3.2,3.3,3.4,3.3))
rownames(x)=c("r1","r2","r3","r4")

library(ggpubr)
## Loading required package: ggplot2
ggballoonplot(x,fill="value")+
  gradient_fill(c("yellow", "red", "green"))

set.seed(2022)
biomasa<-rnorm(120,3,0.3)
trt<-gl(3,40,120,c("t1","t2","t3"))
df=data.frame(biomasa=sort(biomasa),trt=trt)
df
##      biomasa trt
## 1   2.129811  t1
## 2   2.341327  t1
## 3   2.399310  t1
## 4   2.436240  t1
## 5   2.532324  t1
## 6   2.566650  t1
## 7   2.570764  t1
## 8   2.585659  t1
## 9   2.598467  t1
## 10  2.608545  t1
## 11  2.612408  t1
## 12  2.634706  t1
## 13  2.647996  t1
## 14  2.658795  t1
## 15  2.662585  t1
## 16  2.677678  t1
## 17  2.682223  t1
## 18  2.695227  t1
## 19  2.700971  t1
## 20  2.705452  t1
## 21  2.714795  t1
## 22  2.721971  t1
## 23  2.730754  t1
## 24  2.742134  t1
## 25  2.749825  t1
## 26  2.754842  t1
## 27  2.762105  t1
## 28  2.773776  t1
## 29  2.803769  t1
## 30  2.817878  t1
## 31  2.842689  t1
## 32  2.844616  t1
## 33  2.857248  t1
## 34  2.863936  t1
## 35  2.889522  t1
## 36  2.895502  t1
## 37  2.900696  t1
## 38  2.907278  t1
## 39  2.919289  t1
## 40  2.922159  t1
## 41  2.928305  t2
## 42  2.933844  t2
## 43  2.934633  t2
## 44  2.937222  t2
## 45  2.944456  t2
## 46  2.949384  t2
## 47  2.958918  t2
## 48  2.975902  t2
## 49  2.984165  t2
## 50  2.986217  t2
## 51  2.992635  t2
## 52  3.006955  t2
## 53  3.013254  t2
## 54  3.018107  t2
## 55  3.019929  t2
## 56  3.027872  t2
## 57  3.035334  t2
## 58  3.042638  t2
## 59  3.046954  t2
## 60  3.047094  t2
## 61  3.056026  t2
## 62  3.057369  t2
## 63  3.067257  t2
## 64  3.072475  t2
## 65  3.074256  t2
## 66  3.075428  t2
## 67  3.078127  t2
## 68  3.079205  t2
## 69  3.083386  t2
## 70  3.092812  t2
## 71  3.098418  t2
## 72  3.102083  t2
## 73  3.109338  t2
## 74  3.110452  t2
## 75  3.115095  t2
## 76  3.124778  t2
## 77  3.126892  t2
## 78  3.128485  t2
## 79  3.130961  t2
## 80  3.140107  t2
## 81  3.160363  t3
## 82  3.190715  t3
## 83  3.192989  t3
## 84  3.195008  t3
## 85  3.208642  t3
## 86  3.215507  t3
## 87  3.222926  t3
## 88  3.224846  t3
## 89  3.242331  t3
## 90  3.249456  t3
## 91  3.257714  t3
## 92  3.258444  t3
## 93  3.266192  t3
## 94  3.270043  t3
## 95  3.298751  t3
## 96  3.301856  t3
## 97  3.305476  t3
## 98  3.305869  t3
## 99  3.314185  t3
## 100 3.321616  t3
## 101 3.322860  t3
## 102 3.323003  t3
## 103 3.323899  t3
## 104 3.326949  t3
## 105 3.334022  t3
## 106 3.353359  t3
## 107 3.363453  t3
## 108 3.371501  t3
## 109 3.372360  t3
## 110 3.391398  t3
## 111 3.398519  t3
## 112 3.403120  t3
## 113 3.409810  t3
## 114 3.415501  t3
## 115 3.443009  t3
## 116 3.507957  t3
## 117 3.561261  t3
## 118 3.694350  t3
## 119 3.824078  t3
## 120 3.866227  t3
boxplot(df$biomasa~df$trt)

ANOVA

mod=aov(biomasa~trt,data = df)
summary(mod)
##              Df Sum Sq Mean Sq F value Pr(>F)    
## trt           2  8.556   4.278   224.8 <2e-16 ***
## Residuals   117  2.227   0.019                   
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1