Clase 21 deSep Prueba

Variables

nor=(c(48,49,59,49,55,63,45,47,59,39,43,50,54,45,39,24,44,49,46,50,46,50,44,43,50,55,45,36,49,52,45,46,48,41,50,45,51,47,48,55,54,46,55,61,62,50,49,57,45,51,55,57,56,53,50,48,50,41,45,53,62,48,44,45,51,40,42,54,71,48,56,46,50,53,55,46,46,56,49,56,37,37,46,49,49,51,55,37,50,54,37,52,50,42,45,52,58,36,44,58))
nnor=(c(98,98,97,96,95,94,95,96,94,98,96,98,98,96,96,96,98,98,96,95,98,94,94,94,98,94,98,96,96,96,98,97,96,94,98,94,96,94,95,94,98,96,95,94,96,96,94,98,94,98,98,94,98,97,96,98,94,94,97,98,98,94,96,94,98,94,94,97,97,94,94,98,94,98,97,98,96,96,97,94,98,94,96,94,96,97,96,94,98,94,98,96,94,98,95,95,96,96,94,98))
nor25=(c(48,49,59,49,55,63,45,47,59,39,43,50,54,45,39,24,44,49,46,50,46,50,44,43,50))
nnor25=(c(98,98,97,96,95,94,95,96,94,98,96,98,98,96,96,96,98,98,96,95,98,94,94,94,98))
genero=(c(2,1,2,2,1,2,1,1,1,2,2,1,1,1,2,1,2,2,1,1,2,1,2,2,1,1,2,2,1,1,1,2,1,2,1,1,2,1,2,1,2,2,1,2,1,2,1,2,1,2,1,1,1,1,1,2,1,1,1,1,1,2,1,1,2,1,2,2,1,1,2,2,2,2,2,2,1,1,2,2,1,2,1,2,2,2,1,2,2,2,1,2,2,1,2,2,2,1,2,1))
peso=(c(82,84,84,78,76,76,76,76,82,82,84,82,76,76,76,76,82,76,76,84,76,82,76,76,82,84,78,76,82,82,76,82,84,82,76,78,82,80,84,82,82,76,82,82,76,82,76,82,82,84,82,78,82,82,82,84,82,78,82,78,78,76,82,82,82,76,84,76,76,80,76,78,76,82,78,82,76,84,82,84,82,76,80,80,78,82,76,76,76,80,84,76,82,78,76,78,84,84,82,80))

Procedimiento

#Operaciones b?sicas
xb=mean(nor) #Media
s=sd(nor)#Desviaci?n Est?ndar

#Asimetria y Curtosis

library(moments)
skewness(nor) #Coeficiente de Asimetria

## [1] -0.1568576

kurtosis(nor)#Curtosis

## [1] 4.396802

#Gr?ficos de linea
#Criterio- Seguir la linea roja
qqnorm(nor)
qqline(nor,col=2)

hist(nor25, freq = F, col = "blue", xlab = "Balance", main = "",
     xlim = c(xb-4*s, xb+4*s), ylim = c(0, .05), )

curve(dnorm(x, mean = xb, sd = s), col = 2, lwd = 2, add = TRUE)

#Pruebas de normalidad
#Kolmogorov-Smirnov
ks.test(nor, "pnorm", mean = mean(nor), sd = sd(nor))

## Warning in ks.test.default(nor, "pnorm", mean = mean(nor), sd = sd(nor)): ties
## should not be present for the one-sample Kolmogorov-Smirnov test

## 
##  Asymptotic one-sample Kolmogorov-Smirnov test
## 
## data:  nor
## D = 0.082785, p-value = 0.4996
## alternative hypothesis: two-sided

#Anderson-Darlinng [Para muestras muy grandes]
library(nortest)
ad.test(nor)

## 
##  Anderson-Darling normality test
## 
## data:  nor
## A = 0.56271, p-value = 0.1419

#Shapiro-Wilk
shapiro.test(nor25)

## 
##  Shapiro-Wilk normality test
## 
## data:  nor25
## W = 0.9218, p-value = 0.05632