setwd("C:/Users/alex/Documents/R")
getwd()
## [1] "C:/Users/alex/Documents/R"
DTangelica<-read.csv("DTangelica.csv", sep = ";", header = T)#
summary(DTangelica)
## trat epoc rept DVIVOS
## citrico:8 trimestre3:12 Min. :1.00 Min. : 5.00
## H2O :8 Trimestre4:12 1st Qu.:1.75 1st Qu.: 6.60
## MS3K :8 Median :2.50 Median :11.77
## Mean :2.50 Mean :10.69
## 3rd Qu.:3.25 3rd Qu.:13.96
## Max. :4.00 Max. :14.93
## DOXID PCONT BACT HONG
## Min. :0.200 Min. :0.0000 Min. :0.0000 Min. :0.0000
## 1st Qu.:1.195 1st Qu.:0.0675 1st Qu.:0.0000 1st Qu.:0.0000
## Median :1.815 Median :0.1700 Median :0.1300 Median :0.0000
## Mean :1.778 Mean :0.2521 Mean :0.1442 Mean :0.1079
## 3rd Qu.:2.493 3rd Qu.:0.4000 3rd Qu.:0.2000 3rd Qu.:0.2000
## Max. :3.000 Max. :0.6000 Max. :0.6000 Max. :0.4000
## DMUERT ResDVIVOS ResDOXIDA RESPCONT
## Min. :0.0700 Min. :0.03000 Min. :0.0500 Min. :0.100
## 1st Qu.:0.7525 1st Qu.:0.05750 1st Qu.:0.2800 1st Qu.:0.580
## Median :2.2600 Median :0.07000 Median :0.3550 Median :1.610
## Mean :3.8896 Mean :0.07083 Mean :0.3371 Mean :1.194
## 3rd Qu.:7.2000 3rd Qu.:0.09000 3rd Qu.:0.4275 3rd Qu.:1.810
## Max. :9.6000 Max. :0.11000 Max. :0.5800 Max. :1.810
## RESBACT RESHONGO RESDMUERT
## Min. :0.030 Min. :0.420 Min. :0.03000
## 1st Qu.:1.670 1st Qu.:2.040 1st Qu.:0.06000
## Median :2.285 Median :2.040 Median :0.07000
## Mean :1.965 Mean :1.853 Mean :0.07208
## 3rd Qu.:2.450 3rd Qu.:2.180 3rd Qu.:0.09000
## Max. :2.620 Max. :2.530 Max. :0.11000
Permite contrastar la igualdad de varianzas en 2 o más poblaciones sin ser necesario que el tamaño de todas las muestras sea el mismo. Es más sensible que el test de Levene a la falta de normalidad. Pero si se está seguro de que los datos provienen de una distribución normal, es la mejor opción.
library(ggplot2)
library(dplyr)
##
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
##
## filter, lag
## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, union
bartlett.test(DTangelica$ResDVIVOS ~ DTangelica$trat)
##
## Bartlett test of homogeneity of variances
##
## data: DTangelica$ResDVIVOS by DTangelica$trat
## Bartlett's K-squared = 1.5467, df = 2, p-value = 0.4615
bartlett.test(DTangelica$ResDOXIDA ~ DTangelica$trat)
##
## Bartlett test of homogeneity of variances
##
## data: DTangelica$ResDOXIDA by DTangelica$trat
## Bartlett's K-squared = 5.3805, df = 2, p-value = 0.06787
bartlett.test(DTangelica$RESPCONT ~ DTangelica$trat)
##
## Bartlett test of homogeneity of variances
##
## data: DTangelica$RESPCONT by DTangelica$trat
## Bartlett's K-squared = 22.274, df = 2, p-value = 1.456e-05
bartlett.test(DTangelica$RESBACT ~ DTangelica$trat)
##
## Bartlett test of homogeneity of variances
##
## data: DTangelica$RESBACT by DTangelica$trat
## Bartlett's K-squared = 26.102, df = 2, p-value = 2.148e-06
bartlett.test(DTangelica$RESHONGO ~ DTangelica$trat)
##
## Bartlett test of homogeneity of variances
##
## data: DTangelica$RESHONGO by DTangelica$trat
## Bartlett's K-squared = Inf, df = 2, p-value < 2.2e-16
bartlett.test(DTangelica$RESDMUERT ~ DTangelica$trat)
##
## Bartlett test of homogeneity of variances
##
## data: DTangelica$RESDMUERT by DTangelica$trat
## Bartlett's K-squared = 3.288, df = 2, p-value = 0.1932
bartlett.test(DTangelica$ResDVIVOS ~ DTangelica$epoc)
##
## Bartlett test of homogeneity of variances
##
## data: DTangelica$ResDVIVOS by DTangelica$epoc
## Bartlett's K-squared = 2.3609, df = 1, p-value = 0.1244
bartlett.test(DTangelica$ResDOXIDA ~ DTangelica$epoc)
##
## Bartlett test of homogeneity of variances
##
## data: DTangelica$ResDOXIDA by DTangelica$epoc
## Bartlett's K-squared = 2.7014, df = 1, p-value = 0.1003
bartlett.test(DTangelica$RESPCONT ~ DTangelica$epoc)
##
## Bartlett test of homogeneity of variances
##
## data: DTangelica$RESPCONT by DTangelica$epoc
## Bartlett's K-squared = 0.35951, df = 1, p-value = 0.5488
bartlett.test(DTangelica$RESBACT ~ DTangelica$epoc)
##
## Bartlett test of homogeneity of variances
##
## data: DTangelica$RESBACT by DTangelica$epoc
## Bartlett's K-squared = 6.9643, df = 1, p-value = 0.008315
bartlett.test(DTangelica$RESHONGO ~ DTangelica$epoc)
##
## Bartlett test of homogeneity of variances
##
## data: DTangelica$RESHONGO by DTangelica$epoc
## Bartlett's K-squared = 39.771, df = 1, p-value = 2.856e-10
bartlett.test(DTangelica$RESDMUERT ~ DTangelica$epoc)
##
## Bartlett test of homogeneity of variances
##
## data: DTangelica$RESDMUERT by DTangelica$epoc
## Bartlett's K-squared = 4.6243, df = 1, p-value = 0.03152
ggplot(data = DTangelica, aes(x = trat, y = ResDVIVOS, colour = trat)) +
geom_boxplot() + theme_bw()
ggplot(data = DTangelica, aes(x = trat, y = ResDOXIDA, colour = trat)) +
geom_boxplot() + theme_bw()
ggplot(data = DTangelica, aes(x = trat, y = RESPCONT, colour = trat)) +
geom_boxplot() + theme_bw()
ggplot(data = DTangelica, aes(x = trat, y = RESBACT, colour = trat)) +
geom_boxplot() + theme_bw()
ggplot(data = DTangelica, aes(x = trat, y = RESHONGO, colour = trat)) +
geom_boxplot() + theme_bw()
ggplot(data = DTangelica, aes(x = trat, y = RESDMUERT, colour = trat)) +
geom_boxplot() + theme_bw()
Si se tiene seguridad de que existe homogeneidad entre las varianzas de las muestras (ResDVIVOS, ResDOXIDA y RESDMUERT) con un nivel de confianza del p<0.05