#Cargar libreria
library(readr)
## Warning: package 'readr' was built under R version 4.0.3
library (ggplot2)
## Warning: package 'ggplot2' was built under R version 4.0.3
library(resumer)
## Warning: package 'resumer' was built under R version 4.0.3
#Generar Datos
set.seed(2020)
n <- 100
media.edad <- 45; ds.edad <- 10
media.peso <- 75; ds.peso <- 15
media.estatura <- 1.70; ds.estatura <- 0.10
edad <- round(rnorm(n = n, mean = media.edad, sd = ds.edad),0)
peso <- round(rnorm(n = n, mean = media.peso, sd = ds.peso),2)
estatura <- round(rnorm(n = n, mean = media.estatura, sd = ds.estatura),2)
personas <- data.frame(edad, peso, estatura)
head(personas); tail(personas)
## edad peso estatura
## 1 49 49.07 1.63
## 2 48 60.13 1.79
## 3 34 66.22 1.66
## 4 34 80.75 1.74
## 5 17 86.20 1.60
## 6 52 61.07 1.57
## edad peso estatura
## 95 43 64.09 1.73
## 96 37 84.40 1.63
## 97 48 58.63 1.65
## 98 52 67.26 1.88
## 99 40 75.25 1.60
## 100 38 84.91 1.64
#Genera cuartiles
cuartiles <- quantile(personas$edad, probs = c(0.25, 0.50, 0.75), type = 6)
cuartiles[1]
## 25%
## 39
cuartiles[2]
## 50%
## 46
cuartiles[3]
## 75%
## 52.75
cuartiles <- quantile(personas$peso, probs = c(0.25, 0.50, 0.75), type = 6)
cuartiles[1]
## 25%
## 59.53
cuartiles[2]
## 50%
## 74.14
cuartiles[3]
## 75%
## 85.88
cuartiles <- quantile(personas$estatura, probs = c(0.25, 0.50, 0.75), type = 6)
cuartiles[1]
## 25%
## 1.605
cuartiles[2]
## 50%
## 1.69
cuartiles[3]
## 75%
## 1.7675
#PERCENTILES
percentil <- quantile(personas$edad, probs = c(0.10, 0.30, 0.50, 0.70, 0.90), type = 7)
percentil[1]
## 10%
## 32.9
percentil[2]
## 30%
## 41.7
percentil[3]
## 50%
## 46
percentil[4]
## 70%
## 51
percentil[5]
## 90%
## 61.1
percentil <- quantile(personas$peso, probs = c(0.10, 0.30, 0.50, 0.70, 0.90), type = 7)
percentil[1]
## 10%
## 50.902
percentil[2]
## 30%
## 63.302
percentil[3]
## 50%
## 74.14
percentil[4]
## 70%
## 82.613
percentil[5]
## 90%
## 93.698
percentil <- quantile(personas$estatura, probs = c(0.10, 0.30, 0.50, 0.70, 0.90), type = 7)
percentil[1]
## 10%
## 1.548
percentil[2]
## 30%
## 1.63
percentil[3]
## 50%
## 1.69
percentil[4]
## 70%
## 1.75
percentil[5]
## 90%
## 1.821
#GRAFICA LOS DATOS
ggplot(data = personas, aes(edad, colour = 'edad')) +
geom_histogram(position = "stack", bins = 30)
ggplot(data = personas, aes(edad, colour = 'edad')) +
geom_density()
ggplot(data = personas, aes(edad)) +
geom_histogram(bins = 30) +
geom_vline(aes(xintercept = median(edad),
color = "mediana"),
linetype = "dashed",
size = 1) +
geom_vline(aes(xintercept = mean(edad),
color = "media"),
linetype = "dashed",
size = 1) +
labs(title = "Histograma de Edad",subtitle = paste("Media = ", round(mean(edad),2), ", Mediana = ", round(median(edad),2)))
ggplot(data = personas, aes(edad)) +
geom_histogram(bins = 30) +
geom_vline(aes(xintercept = cuartiles[1],
color = "Q1"),
linetype = "dashed",
size = 1) +
geom_vline(aes(xintercept = cuartiles[2],
color = "Q2"),
linetype = "dashed",
size = 1) +
geom_vline(aes(xintercept = cuartiles[3],
color = "Q3"),
linetype = "dashed",
size = 1) +
labs(title = "Histograma de Edad",subtitle = paste("Cuartil 1 al 25% = ",round(cuartiles[1],2), ", Cuartil 2 al 50% = ",round(cuartiles[2],2), ", Cuartil 3 al 75% = ",round(cuartiles[3],2)))
ggplot(data = personas, aes(edad)) +
geom_histogram(bins = 30) +
geom_vline(aes(xintercept = percentil[1],
color = "Perc1"),
linetype = "solid",
size = 2) +
geom_vline(aes(xintercept = percentil[2],
color = "Perc2"),
linetype = "solid",
size = 2) +
geom_vline(aes(xintercept = percentil[3],
color = "Perc3"),
linetype = "solid",
size = 2) +
geom_vline(aes(xintercept = percentil[4],
color = "Perc4"),
linetype = "solid",
size = 2) +
geom_vline(aes(xintercept = percentil[5],
color = "Perc5"),
linetype = "solid",
size = 2) +
labs(title = "Histograma de Edad. Perc = Percentiles",subtitle = paste("Perc al 10% = ",round(percentil[1],2), "Perc al 30% = ",round(percentil[2],2),"Perc al 50% = ",round(percentil[3],2),"Perc al 70% = ",round(percentil[4],2),"Perc al 90% = ",round(percentil[5],2)))