Construir un diagrama de balones que permita visaulizar el comportamiento de la floracion la dosis y la variedad.Usar libreria ggpubr
library(readxl)
library(ggpubr)
## Loading required package: ggplot2
library(ggplot2)
dff<-read_excel("C:\\Users\\yarvis\\Music\\floracion (1).xlsx",sheet = "FLORACION")
yf=cbind(floreada=dff$floreada,no.floreada=dff$total-dff$floreada)
head(yf)
## floreada no.floreada
## [1,] 0 12
## [2,] 0 17
## [3,] 4 6
## [4,] 9 2
## [5,] 10 0
## [6,] 0 17
pf<-dff$floreada/dff$total; pf
## [1] 0.00000000 0.00000000 0.40000000 0.81818182 1.00000000 0.00000000
## [7] 0.20000000 0.50000000 0.90000000 0.50000000 0.14285714 0.06666667
## [13] 0.17647059 0.25000000 1.00000000 0.11111111 0.15789474 0.53571429
## [19] 0.73076923 0.77777778 0.00000000 0.00000000 0.15789474 0.75000000
## [25] 1.00000000 0.00000000 0.08333333 0.00000000 0.06666667 0.00000000
boxplot(pf)
hist(pf, breaks = 20)
pfc<-split(pf,dff$variedad);pfc
## $A
## [1] 0.0000000 0.0000000 0.4000000 0.8181818 1.0000000 0.0000000
##
## $B
## [1] 0.00000000 0.20000000 0.50000000 0.90000000 0.50000000 0.08333333
##
## $C
## [1] 0.14285714 0.06666667 0.17647059 0.25000000 1.00000000 0.00000000
##
## $D
## [1] 0.11111111 0.15789474 0.53571429 0.73076923 0.77777778 0.06666667
##
## $E
## [1] 0.0000000 0.0000000 0.1578947 0.7500000 1.0000000 0.0000000
class(pfc)
## [1] "list"
ball <- data.frame(round(pf, digits = 2), dff$dosis, dff$variedad)
colnames(ball) <- c("prop.flor", "dosis", "variedad")
Realizando diagrama con ggpubr
my_cols <- c("#0D0887FF", "#6A00A8FF", "#B12A90FF",
"#E16462FF", "#FCA636FF", "#F0F921FF")
ggballoonplot(data = ball, y = "dosis", x = "variedad", size = "prop.flor",
fill = "prop.flor") + scale_fill_gradientn(colors = my_cols) +
guides(size = FALSE) + xlab("Dosis") + ylab("Variedad")
dff3= data.frame(dff,pf)
ggdotchart(dff3, x="dosis", y="pf", xlab = "Dosis", ylab = "Proporción de Floración", color= "variedad",legend="left")
Probar que los residuales tienen distribucion Gamma.
muertos<- read_excel("C:\\Users\\yarvis\\Music\\muertos (1).xlsx",sheet = "muertos")
dfmu=data.frame(muertos)
vari.t<-tapply(dfmu$tiempo,dfmu$tratamiento,var);vari.t
## alta bajo control
## 60.0098 119.0204 356.4147
Se obtienen los residuales para hacer la prueba:
modg<-aov(dfmu$tiempo~dfmu$tratamiento)
summary(modg)
## Df Sum Sq Mean Sq F value Pr(>F)
## dfmu$tratamiento 2 43167 21584 120.9 <2e-16 ***
## Residuals 147 26237 178
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
res<-modg$residuals
hist(res)
plot(res)