data(iris)
summary(iris)
## Sepal.Length Sepal.Width Petal.Length Petal.Width
## Min. :4.300 Min. :2.000 Min. :1.000 Min. :0.100
## 1st Qu.:5.100 1st Qu.:2.800 1st Qu.:1.600 1st Qu.:0.300
## Median :5.800 Median :3.000 Median :4.350 Median :1.300
## Mean :5.843 Mean :3.057 Mean :3.758 Mean :1.199
## 3rd Qu.:6.400 3rd Qu.:3.300 3rd Qu.:5.100 3rd Qu.:1.800
## Max. :7.900 Max. :4.400 Max. :6.900 Max. :2.500
## Species
## setosa :50
## versicolor:50
## virginica :50
##
##
##
En la anterior tabla se presentan las estadisticas descriptivas del conjunto de datos iris, se observa que existen 50 muestras por cada especie.
library(ggplot2)
ggplot(iris, aes(x=Sepal.Length))+
geom_histogram(fill="red")
## `stat_bin()` using `bins = 30`. Pick better value `binwidth`.
ggplot(iris, aes(x=Sepal.Width))+
geom_histogram(fill="blue")
## `stat_bin()` using `bins = 30`. Pick better value `binwidth`.
ggplot(iris, aes(x=Petal.Length))+
geom_histogram(fill="green")
## `stat_bin()` using `bins = 30`. Pick better value `binwidth`.
ggplot(iris, aes(x=Petal.Width))+
geom_histogram(fill="gold")
## `stat_bin()` using `bins = 30`. Pick better value `binwidth`.
## `stat_bin()` using `bins = 30`. Pick better value `binwidth`.
## `stat_bin()` using `bins = 30`. Pick better value `binwidth`.
ggplot(iris, aes(y=Sepal.Length, x=Species, fill=Species))+
geom_boxplot()
ggplot(iris, aes(y=Sepal.Width, x=Species, fill=Species))+
geom_boxplot()
ggplot(iris, aes(y=Petal.Length, x=Species, fill=Species))+
geom_boxplot()
ggplot(iris, aes(y=Petal.Width, x=Species, fill=Species))+
geom_boxplot()
ggplot(iris, aes(x=Sepal.Length, y=Petal.Length))+
geom_jitter()+
geom_smooth(method="lm", colour="red")
## `geom_smooth()` using formula = 'y ~ x'
cor(iris$Sepal.Length, iris$Petal.Length)
## [1] 0.8717538
Encabezado Tabla | Segundo Encabezado |
---|---|
Celda de tabla | Celda 2 |
Celda 3 | Celda 4 |