## formato ancho de los datos, es recomendable usar el formato largo
tallerfinal2 <- read.delim('clipboard')
(tallerfinal2 = within(tallerfinal2, {
id <- factor(id)
}))
## cultivar stress rto60d rto70d rto80d id
## 1 c1 p 24.35 55.99 79.59 1
## 2 c1 p 27.41 63.72 88.76 2
## 3 c1 p 31.04 67.68 90.07 3
## 4 c1 p 32.78 72.73 92.54 4
## 5 c1 p 33.34 73.92 93.10 5
## 6 c1 a 33.44 79.80 93.21 6
## 7 c1 a 36.15 82.88 93.97 7
## 8 c1 a 36.21 84.31 95.30 8
## 9 c1 a 36.98 84.61 95.98 9
## 10 c1 a 39.27 84.84 97.98 10
## 11 c2 p 40.83 86.37 99.04 11
## 12 c2 p 41.23 88.62 102.82 12
## 13 c2 p 44.04 94.21 115.12 13
## 14 c2 p 46.38 91.21 117.42 14
## 15 c2 p 48.24 94.19 121.49 15
## 16 c2 a 48.47 94.23 121.66 16
## 17 c2 a 48.72 97.49 125.47 17
## 18 c2 a 49.98 99.21 126.07 18
## 19 c2 a 51.06 99.43 124.14 19
## 20 c2 a 57.35 100.66 127.63 20
## 21 c1 p 57.88 102.05 128.82 21
## 22 c1 p 58.36 102.51 134.53 22
## 23 c1 p 58.83 105.48 134.59 23
## 24 c1 p 61.28 109.52 138.81 24
## 25 c1 p 67.52 110.11 142.22 25
## 26 c2 a 67.97 111.29 146.67 26
## 27 c2 a 70.23 111.50 147.79 27
## 28 c2 a 73.21 111.76 151.74 28
## 29 c2 a 78.56 112.22 161.42 29
## 30 c2 a 90.13 119.61 180.09 30
par(cex = .6)
unique(tallerfinal2$stress)
## [1] "p" "a"
unique(tallerfinal2$cultivar)
## [1] "c1" "c2"
unique(tallerfinal2$id)
## [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25
## [26] 26 27 28 29 30
## 30 Levels: 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 ... 30
## formato largo
library(tidyr)
(tallerfinal3 <- tallerfinal2 %>%
gather(key = "tiempo_dias", value = "rto", 3:5))
## cultivar stress id tiempo_dias rto
## 1 c1 p 1 rto60d 24.35
## 2 c1 p 2 rto60d 27.41
## 3 c1 p 3 rto60d 31.04
## 4 c1 p 4 rto60d 32.78
## 5 c1 p 5 rto60d 33.34
## 6 c1 a 6 rto60d 33.44
## 7 c1 a 7 rto60d 36.15
## 8 c1 a 8 rto60d 36.21
## 9 c1 a 9 rto60d 36.98
## 10 c1 a 10 rto60d 39.27
## 11 c2 p 11 rto60d 40.83
## 12 c2 p 12 rto60d 41.23
## 13 c2 p 13 rto60d 44.04
## 14 c2 p 14 rto60d 46.38
## 15 c2 p 15 rto60d 48.24
## 16 c2 a 16 rto60d 48.47
## 17 c2 a 17 rto60d 48.72
## 18 c2 a 18 rto60d 49.98
## 19 c2 a 19 rto60d 51.06
## 20 c2 a 20 rto60d 57.35
## 21 c1 p 21 rto60d 57.88
## 22 c1 p 22 rto60d 58.36
## 23 c1 p 23 rto60d 58.83
## 24 c1 p 24 rto60d 61.28
## 25 c1 p 25 rto60d 67.52
## 26 c2 a 26 rto60d 67.97
## 27 c2 a 27 rto60d 70.23
## 28 c2 a 28 rto60d 73.21
## 29 c2 a 29 rto60d 78.56
## 30 c2 a 30 rto60d 90.13
## 31 c1 p 1 rto70d 55.99
## 32 c1 p 2 rto70d 63.72
## 33 c1 p 3 rto70d 67.68
## 34 c1 p 4 rto70d 72.73
## 35 c1 p 5 rto70d 73.92
## 36 c1 a 6 rto70d 79.80
## 37 c1 a 7 rto70d 82.88
## 38 c1 a 8 rto70d 84.31
## 39 c1 a 9 rto70d 84.61
## 40 c1 a 10 rto70d 84.84
## 41 c2 p 11 rto70d 86.37
## 42 c2 p 12 rto70d 88.62
## 43 c2 p 13 rto70d 94.21
## 44 c2 p 14 rto70d 91.21
## 45 c2 p 15 rto70d 94.19
## 46 c2 a 16 rto70d 94.23
## 47 c2 a 17 rto70d 97.49
## 48 c2 a 18 rto70d 99.21
## 49 c2 a 19 rto70d 99.43
## 50 c2 a 20 rto70d 100.66
## 51 c1 p 21 rto70d 102.05
## 52 c1 p 22 rto70d 102.51
## 53 c1 p 23 rto70d 105.48
## 54 c1 p 24 rto70d 109.52
## 55 c1 p 25 rto70d 110.11
## 56 c2 a 26 rto70d 111.29
## 57 c2 a 27 rto70d 111.50
## 58 c2 a 28 rto70d 111.76
## 59 c2 a 29 rto70d 112.22
## 60 c2 a 30 rto70d 119.61
## 61 c1 p 1 rto80d 79.59
## 62 c1 p 2 rto80d 88.76
## 63 c1 p 3 rto80d 90.07
## 64 c1 p 4 rto80d 92.54
## 65 c1 p 5 rto80d 93.10
## 66 c1 a 6 rto80d 93.21
## 67 c1 a 7 rto80d 93.97
## 68 c1 a 8 rto80d 95.30
## 69 c1 a 9 rto80d 95.98
## 70 c1 a 10 rto80d 97.98
## 71 c2 p 11 rto80d 99.04
## 72 c2 p 12 rto80d 102.82
## 73 c2 p 13 rto80d 115.12
## 74 c2 p 14 rto80d 117.42
## 75 c2 p 15 rto80d 121.49
## 76 c2 a 16 rto80d 121.66
## 77 c2 a 17 rto80d 125.47
## 78 c2 a 18 rto80d 126.07
## 79 c2 a 19 rto80d 124.14
## 80 c2 a 20 rto80d 127.63
## 81 c1 p 21 rto80d 128.82
## 82 c1 p 22 rto80d 134.53
## 83 c1 p 23 rto80d 134.59
## 84 c1 p 24 rto80d 138.81
## 85 c1 p 25 rto80d 142.22
## 86 c2 a 26 rto80d 146.67
## 87 c2 a 27 rto80d 147.79
## 88 c2 a 28 rto80d 151.74
## 89 c2 a 29 rto80d 161.42
## 90 c2 a 30 rto80d 180.09
(tallerfinal3 = within(tallerfinal3, {
tiempo_dias <- factor(tiempo_dias)
}))
## cultivar stress id tiempo_dias rto
## 1 c1 p 1 rto60d 24.35
## 2 c1 p 2 rto60d 27.41
## 3 c1 p 3 rto60d 31.04
## 4 c1 p 4 rto60d 32.78
## 5 c1 p 5 rto60d 33.34
## 6 c1 a 6 rto60d 33.44
## 7 c1 a 7 rto60d 36.15
## 8 c1 a 8 rto60d 36.21
## 9 c1 a 9 rto60d 36.98
## 10 c1 a 10 rto60d 39.27
## 11 c2 p 11 rto60d 40.83
## 12 c2 p 12 rto60d 41.23
## 13 c2 p 13 rto60d 44.04
## 14 c2 p 14 rto60d 46.38
## 15 c2 p 15 rto60d 48.24
## 16 c2 a 16 rto60d 48.47
## 17 c2 a 17 rto60d 48.72
## 18 c2 a 18 rto60d 49.98
## 19 c2 a 19 rto60d 51.06
## 20 c2 a 20 rto60d 57.35
## 21 c1 p 21 rto60d 57.88
## 22 c1 p 22 rto60d 58.36
## 23 c1 p 23 rto60d 58.83
## 24 c1 p 24 rto60d 61.28
## 25 c1 p 25 rto60d 67.52
## 26 c2 a 26 rto60d 67.97
## 27 c2 a 27 rto60d 70.23
## 28 c2 a 28 rto60d 73.21
## 29 c2 a 29 rto60d 78.56
## 30 c2 a 30 rto60d 90.13
## 31 c1 p 1 rto70d 55.99
## 32 c1 p 2 rto70d 63.72
## 33 c1 p 3 rto70d 67.68
## 34 c1 p 4 rto70d 72.73
## 35 c1 p 5 rto70d 73.92
## 36 c1 a 6 rto70d 79.80
## 37 c1 a 7 rto70d 82.88
## 38 c1 a 8 rto70d 84.31
## 39 c1 a 9 rto70d 84.61
## 40 c1 a 10 rto70d 84.84
## 41 c2 p 11 rto70d 86.37
## 42 c2 p 12 rto70d 88.62
## 43 c2 p 13 rto70d 94.21
## 44 c2 p 14 rto70d 91.21
## 45 c2 p 15 rto70d 94.19
## 46 c2 a 16 rto70d 94.23
## 47 c2 a 17 rto70d 97.49
## 48 c2 a 18 rto70d 99.21
## 49 c2 a 19 rto70d 99.43
## 50 c2 a 20 rto70d 100.66
## 51 c1 p 21 rto70d 102.05
## 52 c1 p 22 rto70d 102.51
## 53 c1 p 23 rto70d 105.48
## 54 c1 p 24 rto70d 109.52
## 55 c1 p 25 rto70d 110.11
## 56 c2 a 26 rto70d 111.29
## 57 c2 a 27 rto70d 111.50
## 58 c2 a 28 rto70d 111.76
## 59 c2 a 29 rto70d 112.22
## 60 c2 a 30 rto70d 119.61
## 61 c1 p 1 rto80d 79.59
## 62 c1 p 2 rto80d 88.76
## 63 c1 p 3 rto80d 90.07
## 64 c1 p 4 rto80d 92.54
## 65 c1 p 5 rto80d 93.10
## 66 c1 a 6 rto80d 93.21
## 67 c1 a 7 rto80d 93.97
## 68 c1 a 8 rto80d 95.30
## 69 c1 a 9 rto80d 95.98
## 70 c1 a 10 rto80d 97.98
## 71 c2 p 11 rto80d 99.04
## 72 c2 p 12 rto80d 102.82
## 73 c2 p 13 rto80d 115.12
## 74 c2 p 14 rto80d 117.42
## 75 c2 p 15 rto80d 121.49
## 76 c2 a 16 rto80d 121.66
## 77 c2 a 17 rto80d 125.47
## 78 c2 a 18 rto80d 126.07
## 79 c2 a 19 rto80d 124.14
## 80 c2 a 20 rto80d 127.63
## 81 c1 p 21 rto80d 128.82
## 82 c1 p 22 rto80d 134.53
## 83 c1 p 23 rto80d 134.59
## 84 c1 p 24 rto80d 138.81
## 85 c1 p 25 rto80d 142.22
## 86 c2 a 26 rto80d 146.67
## 87 c2 a 27 rto80d 147.79
## 88 c2 a 28 rto80d 151.74
## 89 c2 a 29 rto80d 161.42
## 90 c2 a 30 rto80d 180.09
par(cex = .6)
modelo <- aov(rto ~ cultivar * stress + Error(id), data = tallerfinal3)
summary(modelo)
##
## Error: id
## Df Sum Sq Mean Sq F value Pr(>F)
## cultivar 1 7517 7517 11.017 0.00268 **
## stress 1 695 695 1.018 0.32218
## cultivar:stress 1 4836 4836 7.088 0.01313 *
## Residuals 26 17740 682
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Error: Within
## Df Sum Sq Mean Sq F value Pr(>F)
## Residuals 60 75738 1262
with(tallerfinal3, interaction.plot(cultivar, stress, rto,
ylim = c(5, 200), lty= c(1, 10), lwd = 3,
ylab = "mean of rto", xlab = "cultivar", trace.label = "stress"))
Caso A: sin factor
library(ggplot2)
ggplot(tallerfinal3)+
aes(tiempo_dias, rto)+
stat_boxplot(geom = "errorbar", width = 0.2) +
geom_boxplot(fill=5, outlier.colour = "red")+
labs(x='Tiempo en dias', y='Rendimiento')+
stat_summary(fun = "mean", geom = "point", shape = 8,
size = 2, color = "red")+
geom_smooth(method='lm', se=F)
## `geom_smooth()` using formula 'y ~ x'
## para este caso, el rendimiento en el peso seco de uchuva es mayor a los 80 dias después del cuajamiento del fruto
library(ggpubr)
library(rstatix)
##
## Attaching package: 'rstatix'
## The following object is masked from 'package:stats':
##
## filter
modcasoA <- anova_test(data = tallerfinal3, dv = rto, wid = id, within = tiempo_dias)
get_anova_table(modcasoA)
## ANOVA Table (type III tests)
##
## Effect DFn DFd F p p<.05 ges
## 1 tiempo_dias 1.34 38.81 917.162 1.19e-30 * 0.689
caso B: Con el factor Cultivar (C1:dorada-C2:andina)
(tallerfinal4 = within(tallerfinal3, {
stress <- factor(stress)
cultivar <- factor(cultivar)
}))
## cultivar stress id tiempo_dias rto
## 1 c1 p 1 rto60d 24.35
## 2 c1 p 2 rto60d 27.41
## 3 c1 p 3 rto60d 31.04
## 4 c1 p 4 rto60d 32.78
## 5 c1 p 5 rto60d 33.34
## 6 c1 a 6 rto60d 33.44
## 7 c1 a 7 rto60d 36.15
## 8 c1 a 8 rto60d 36.21
## 9 c1 a 9 rto60d 36.98
## 10 c1 a 10 rto60d 39.27
## 11 c2 p 11 rto60d 40.83
## 12 c2 p 12 rto60d 41.23
## 13 c2 p 13 rto60d 44.04
## 14 c2 p 14 rto60d 46.38
## 15 c2 p 15 rto60d 48.24
## 16 c2 a 16 rto60d 48.47
## 17 c2 a 17 rto60d 48.72
## 18 c2 a 18 rto60d 49.98
## 19 c2 a 19 rto60d 51.06
## 20 c2 a 20 rto60d 57.35
## 21 c1 p 21 rto60d 57.88
## 22 c1 p 22 rto60d 58.36
## 23 c1 p 23 rto60d 58.83
## 24 c1 p 24 rto60d 61.28
## 25 c1 p 25 rto60d 67.52
## 26 c2 a 26 rto60d 67.97
## 27 c2 a 27 rto60d 70.23
## 28 c2 a 28 rto60d 73.21
## 29 c2 a 29 rto60d 78.56
## 30 c2 a 30 rto60d 90.13
## 31 c1 p 1 rto70d 55.99
## 32 c1 p 2 rto70d 63.72
## 33 c1 p 3 rto70d 67.68
## 34 c1 p 4 rto70d 72.73
## 35 c1 p 5 rto70d 73.92
## 36 c1 a 6 rto70d 79.80
## 37 c1 a 7 rto70d 82.88
## 38 c1 a 8 rto70d 84.31
## 39 c1 a 9 rto70d 84.61
## 40 c1 a 10 rto70d 84.84
## 41 c2 p 11 rto70d 86.37
## 42 c2 p 12 rto70d 88.62
## 43 c2 p 13 rto70d 94.21
## 44 c2 p 14 rto70d 91.21
## 45 c2 p 15 rto70d 94.19
## 46 c2 a 16 rto70d 94.23
## 47 c2 a 17 rto70d 97.49
## 48 c2 a 18 rto70d 99.21
## 49 c2 a 19 rto70d 99.43
## 50 c2 a 20 rto70d 100.66
## 51 c1 p 21 rto70d 102.05
## 52 c1 p 22 rto70d 102.51
## 53 c1 p 23 rto70d 105.48
## 54 c1 p 24 rto70d 109.52
## 55 c1 p 25 rto70d 110.11
## 56 c2 a 26 rto70d 111.29
## 57 c2 a 27 rto70d 111.50
## 58 c2 a 28 rto70d 111.76
## 59 c2 a 29 rto70d 112.22
## 60 c2 a 30 rto70d 119.61
## 61 c1 p 1 rto80d 79.59
## 62 c1 p 2 rto80d 88.76
## 63 c1 p 3 rto80d 90.07
## 64 c1 p 4 rto80d 92.54
## 65 c1 p 5 rto80d 93.10
## 66 c1 a 6 rto80d 93.21
## 67 c1 a 7 rto80d 93.97
## 68 c1 a 8 rto80d 95.30
## 69 c1 a 9 rto80d 95.98
## 70 c1 a 10 rto80d 97.98
## 71 c2 p 11 rto80d 99.04
## 72 c2 p 12 rto80d 102.82
## 73 c2 p 13 rto80d 115.12
## 74 c2 p 14 rto80d 117.42
## 75 c2 p 15 rto80d 121.49
## 76 c2 a 16 rto80d 121.66
## 77 c2 a 17 rto80d 125.47
## 78 c2 a 18 rto80d 126.07
## 79 c2 a 19 rto80d 124.14
## 80 c2 a 20 rto80d 127.63
## 81 c1 p 21 rto80d 128.82
## 82 c1 p 22 rto80d 134.53
## 83 c1 p 23 rto80d 134.59
## 84 c1 p 24 rto80d 138.81
## 85 c1 p 25 rto80d 142.22
## 86 c2 a 26 rto80d 146.67
## 87 c2 a 27 rto80d 147.79
## 88 c2 a 28 rto80d 151.74
## 89 c2 a 29 rto80d 161.42
## 90 c2 a 30 rto80d 180.09
library(ggplot2)
ggplot(tallerfinal4,
aes(tiempo_dias, rto))+
geom_boxplot(aes(fill=cultivar, outlier.colour = "red"))+
labs(x='Tiempo en dias', y='Rendimiento')+
stat_summary(fun = "cultivar", geom = "point", shape = 8,
size = 2, color = "red")+
geom_smooth(method='lm', se=F)
## Warning: Ignoring unknown aesthetics: outlier.colour
## Warning: Computation failed in `stat_summary()`:
## el objeto 'cultivar' de modo 'function' no fue encontrado
## `geom_smooth()` using formula 'y ~ x'
## Grafico de interacción entre las dos especies
interaction.plot(tallerfinal4$tiempo_dias, tallerfinal4$cultivar, tallerfinal4$rto, xlab = "Tiempo (días)", ylab = "Rendimiento", col = c("red", "blue"), trace.label = "especie")
