Para este ejercicio en R usaremos datos del producto intero bruto (PIB) del estado de Sonora, México (2010-2019) estos datos pueden ser encotrados en este enalce:
https://hacienda.sonora.gob.mx/finanzas-publicas/estadisticas/
PIB <- c(385751, 446699, 488558, 510316, 531147, 588735, 663323, 724400, 762760, 773685 )
sort(PIB, decreasing = TRUE)
## [1] 773685 762760 724400 663323 588735 531147 510316 488558 446699 385751
sort(PIB, decreasing = FALSE )
## [1] 385751 446699 488558 510316 531147 588735 663323 724400 762760 773685
library(fdth)
##
## Attaching package: 'fdth'
## The following objects are masked from 'package:stats':
##
## sd, var
tabla <- fdt(PIB)
tabla
## Class limits f rf rf(%) cf cf(%)
## [381893.49,461799.162) 2 0.2 20 2 20
## [461799.162,541704.834) 3 0.3 30 5 50
## [541704.834,621610.506) 1 0.1 10 6 60
## [621610.506,701516.178) 1 0.1 10 7 70
## [701516.178,781421.85) 3 0.3 30 10 100
#histograma
plot(tabla,type='fh') # Absolute frequency histogram
*Poligono
plot(tabla,type='fp') # Absolute frequency histogram
plot(tabla,type='rfh') # Relative frequency histogram
plot(tabla,type='rfp') # Absolute frequency histogram
plot(tabla,type='cfh') # Relative frequency histogram
plot(tabla,type='cfp') # Relative frequency histogram
mean(PIB)
## [1] 587537.4
median(PIB)
## [1] 559941
library(modeest)
##
## Attaching package: 'modeest'
## The following object is masked from 'package:fdth':
##
## mfv
mlv(PIB, method = "mfv")
## [1] 385751 446699 488558 510316 531147 588735 663323 724400 762760 773685
summary(PIB)
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 385751 493998 559941 587537 709131 773685
boxplot(PIB)