library(readxl)
Datos_papa <- read_excel("C:/Users/luisc/Downloads/Datos_papa.xlsx",
sheet = "Hoja 1")
View(Datos_papa)Anova para peso en el aire
# peso en el aire
m1 <- aov(Peso_en_aire~Trat, data = Datos_papa)
anova(m1)## Analysis of Variance Table
##
## Response: Peso_en_aire
## Df Sum Sq Mean Sq F value Pr(>F)
## Trat 2 34637 17318.3 358.23 5.728e-07 ***
## Residuals 6 290 48.3
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1m7 <- kruskal.test(Datos_papa$Peso_en_aire, Datos_papa$Trat, alpha = 0.05)
m7##
## Kruskal-Wallis rank sum test
##
## data: Datos_papa$Peso_en_aire and Datos_papa$Trat
## Kruskal-Wallis chi-squared = 7.2, df = 2, p-value = 0.02732#Prueba de normalidad
shapiro.test(resid(m1))##
## Shapiro-Wilk normality test
##
## data: resid(m1)
## W = 0.98402, p-value = 0.9817library(car)## Loading required package: carDatalibrary(carData)#Prueba de homogeneidad de varianza tambien homocedasticidad
leveneTest(Datos_papa$Peso_en_aire~Datos_papa$Trat, center=mean)## Warning in leveneTest.default(y = y, group = group, ...): group coerced to
## factor.## Levene's Test for Homogeneity of Variance (center = mean)
## Df F value Pr(>F)
## group 2 1.2045 0.3633
## 6library(agricolae)
library(dplyr)##
## Attaching package: 'dplyr'## The following object is masked from 'package:car':
##
## recode## The following objects are masked from 'package:stats':
##
## filter, lag## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, unionm1Tukey <-HSD.test(Datos_papa$Peso_en_aire, Datos_papa$Trat, 6, 48.3, alpha = 0.05)
m1Tukey## $statistics
## MSerror Df Mean CV MSD
## 48.3 6 119.8278 5.799841 17.41094
##
## $parameters
## test name.t ntr StudentizedRange alpha
## Tukey Datos_papa$Trat 3 4.339195 0.05
##
## $means
## Datos_papa$Peso_en_aire std r Min Max Q25 Q50
## Capiro 196.46333 9.952549 3 185.91 205.68 191.855 197.80
## Criolla 44.52333 3.755720 3 40.54 48.00 42.785 45.03
## Sabanera 118.49667 5.645709 3 112.80 124.09 115.700 118.60
## Q75
## Capiro 201.740
## Criolla 46.515
## Sabanera 121.345
##
## $comparison
## NULL
##
## $groups
## Datos_papa$Peso_en_aire groups
## Capiro 196.46333 a
## Sabanera 118.49667 b
## Criolla 44.52333 c
##
## attr(,"class")
## [1] "group"m9LSD <- LSD.test(Datos_papa$Peso_en_aire, Datos_papa$Trat, 6, 48.3, alpha = 0.05)
m9LSD## $statistics
## MSerror Df Mean CV t.value LSD
## 48.3 6 119.8278 5.799841 2.446912 13.88501
##
## $parameters
## test p.ajusted name.t ntr alpha
## Fisher-LSD none Datos_papa$Trat 3 0.05
##
## $means
## Datos_papa$Peso_en_aire std r LCL UCL Min Max
## Capiro 196.46333 9.952549 3 186.64515 206.28152 185.91 205.68
## Criolla 44.52333 3.755720 3 34.70515 54.34152 40.54 48.00
## Sabanera 118.49667 5.645709 3 108.67848 128.31485 112.80 124.09
## Q25 Q50 Q75
## Capiro 191.855 197.80 201.740
## Criolla 42.785 45.03 46.515
## Sabanera 115.700 118.60 121.345
##
## $comparison
## NULL
##
## $groups
## Datos_papa$Peso_en_aire groups
## Capiro 196.46333 a
## Sabanera 118.49667 b
## Criolla 44.52333 c
##
## attr(,"class")
## [1] "group"Peso en el agua
#Peso en agua
m2 <- aov(Peso_en_agua~Trat, data = Datos_papa)
anova(m2)## Analysis of Variance Table
##
## Response: Peso_en_agua
## Df Sum Sq Mean Sq F value Pr(>F)
## Trat 2 222.406 111.203 66.675 7.983e-05 ***
## Residuals 6 10.007 1.668
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1shapiro.test(resid(m2))##
## Shapiro-Wilk normality test
##
## data: resid(m2)
## W = 0.84847, p-value = 0.07169leveneTest(Datos_papa$Peso_en_agua~Datos_papa$Trat, center=mean)## Warning in leveneTest.default(y = y, group = group, ...): group coerced to
## factor.## Levene's Test for Homogeneity of Variance (center = mean)
## Df F value Pr(>F)
## group 2 4.2978 0.06947 .
## 6
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1m2Tukey <-HSD.test(Datos_papa$Peso_en_agua, Datos_papa$Trat, 6, 1.668, alpha = 0.05)
m2Tukey## $statistics
## MSerror Df Mean CV MSD
## 1.668 6 9.955556 12.97276 3.235539
##
## $parameters
## test name.t ntr StudentizedRange alpha
## Tukey Datos_papa$Trat 3 4.339195 0.05
##
## $means
## Datos_papa$Peso_en_agua std r Min Max Q25 Q50 Q75
## Capiro 15.89667 2.1987345 3 13.57 17.94 14.875 16.18 17.060
## Criolla 3.73000 0.2306513 3 3.55 3.99 3.600 3.65 3.820
## Sabanera 10.24000 0.3404409 3 9.87 10.54 10.090 10.31 10.425
##
## $comparison
## NULL
##
## $groups
## Datos_papa$Peso_en_agua groups
## Capiro 15.89667 a
## Sabanera 10.24000 b
## Criolla 3.73000 c
##
## attr(,"class")
## [1] "group"o9LSD <- LSD.test(Datos_papa$Peso_en_agua, Datos_papa$Trat, 6, 1.668, alpha = 0.05)
o9LSD## $statistics
## MSerror Df Mean CV t.value LSD
## 1.668 6 9.955556 12.97276 2.446912 2.580303
##
## $parameters
## test p.ajusted name.t ntr alpha
## Fisher-LSD none Datos_papa$Trat 3 0.05
##
## $means
## Datos_papa$Peso_en_agua std r LCL UCL Min Max
## Capiro 15.89667 2.1987345 3 14.07212 17.72122 13.57 17.94
## Criolla 3.73000 0.2306513 3 1.90545 5.55455 3.55 3.99
## Sabanera 10.24000 0.3404409 3 8.41545 12.06455 9.87 10.54
## Q25 Q50 Q75
## Capiro 14.875 16.18 17.060
## Criolla 3.600 3.65 3.820
## Sabanera 10.090 10.31 10.425
##
## $comparison
## NULL
##
## $groups
## Datos_papa$Peso_en_agua groups
## Capiro 15.89667 a
## Sabanera 10.24000 b
## Criolla 3.73000 c
##
## attr(,"class")
## [1] "group"m10duncan <- duncan.test(Datos_papa$Peso_en_agua, Datos_papa$Trat, 6, 1.668, alpha = 0.05)
m10duncan## $statistics
## MSerror Df Mean CV
## 1.668 6 9.955556 12.97276
##
## $parameters
## test name.t ntr alpha
## Duncan Datos_papa$Trat 3 0.05
##
## $duncan
## Table CriticalRange
## 2 3.460456 2.580303
## 3 3.586498 2.674287
##
## $means
## Datos_papa$Peso_en_agua std r Min Max Q25 Q50 Q75
## Capiro 15.89667 2.1987345 3 13.57 17.94 14.875 16.18 17.060
## Criolla 3.73000 0.2306513 3 3.55 3.99 3.600 3.65 3.820
## Sabanera 10.24000 0.3404409 3 9.87 10.54 10.090 10.31 10.425
##
## $comparison
## NULL
##
## $groups
## Datos_papa$Peso_en_agua groups
## Capiro 15.89667 a
## Sabanera 10.24000 b
## Criolla 3.73000 c
##
## attr(,"class")
## [1] "group"Indice de color
#indice de color
m3 <- aov(Indice_color~Trat, data = Datos_papa)
anova(m3)## Analysis of Variance Table
##
## Response: Indice_color
## Df Sum Sq Mean Sq F value Pr(>F)
## Trat 2 4.2254 2.1127 0.9837 0.4271
## Residuals 6 12.8858 2.1476shapiro.test(resid(m3))##
## Shapiro-Wilk normality test
##
## data: resid(m3)
## W = 0.9112, p-value = 0.3244leveneTest(Datos_papa$Indice_color~Datos_papa$Trat, center=mean)## Warning in leveneTest.default(y = y, group = group, ...): group coerced to
## factor.## Levene's Test for Homogeneity of Variance (center = mean)
## Df F value Pr(>F)
## group 2 5.0378 0.05199 .
## 6
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1m3Tukey <-HSD.test(Datos_papa$Indice_color, Datos_papa$Trat, 12, 2.1476, alpha = 0.05)
m3Tukey## $statistics
## MSerror Df Mean CV MSD
## 2.1476 12 0.355374 412.3738 3.192234
##
## $parameters
## test name.t ntr StudentizedRange alpha
## Tukey Datos_papa$Trat 3 3.772929 0.05
##
## $means
## Datos_papa$Indice_color std r Min Max Q25
## Capiro 1.0483704 0.6888142 3 0.4191904 1.7843443 0.6803835
## Criolla 0.5954273 0.3034253 3 0.3962511 0.9446422 0.4208199
## Sabanera -0.5776758 2.4241267 3 -2.6306000 2.0966688 -1.9148481
## Q50 Q75
## Capiro 0.9415766 1.3629604
## Criolla 0.4453887 0.6950155
## Sabanera -1.1990962 0.4487863
##
## $comparison
## NULL
##
## $groups
## Datos_papa$Indice_color groups
## Capiro 1.0483704 a
## Criolla 0.5954273 a
## Sabanera -0.5776758 a
##
## attr(,"class")
## [1] "group"m91LSD <- LSD.test(Datos_papa$Indice_color, Datos_papa$Trat, 12, 2.1476, alpha = 0.05)
m91LSD## $statistics
## MSerror Df Mean CV t.value LSD
## 2.1476 12 0.355374 412.3738 2.178813 2.60706
##
## $parameters
## test p.ajusted name.t ntr alpha
## Fisher-LSD none Datos_papa$Trat 3 0.05
##
## $means
## Datos_papa$Indice_color std r LCL UCL Min
## Capiro 1.0483704 0.6888142 3 -0.7950992 2.891840 0.4191904
## Criolla 0.5954273 0.3034253 3 -1.2480423 2.438897 0.3962511
## Sabanera -0.5776758 2.4241267 3 -2.4211455 1.265794 -2.6306000
## Max Q25 Q50 Q75
## Capiro 1.7843443 0.6803835 0.9415766 1.3629604
## Criolla 0.9446422 0.4208199 0.4453887 0.6950155
## Sabanera 2.0966688 -1.9148481 -1.1990962 0.4487863
##
## $comparison
## NULL
##
## $groups
## Datos_papa$Indice_color groups
## Capiro 1.0483704 a
## Criolla 0.5954273 a
## Sabanera -0.5776758 a
##
## attr(,"class")
## [1] "group"m92duncan <- duncan.test(Datos_papa$Indice_color, Datos_papa$Trat, 12, 2.1476, alpha = 0.05)
m92duncan## $statistics
## MSerror Df Mean CV
## 2.1476 12 0.355374 412.3738
##
## $parameters
## test name.t ntr alpha
## Duncan Datos_papa$Trat 3 0.05
##
## $duncan
## Table CriticalRange
## 2 3.081307 2.607060
## 3 3.225244 2.728843
##
## $means
## Datos_papa$Indice_color std r Min Max Q25
## Capiro 1.0483704 0.6888142 3 0.4191904 1.7843443 0.6803835
## Criolla 0.5954273 0.3034253 3 0.3962511 0.9446422 0.4208199
## Sabanera -0.5776758 2.4241267 3 -2.6306000 2.0966688 -1.9148481
## Q50 Q75
## Capiro 0.9415766 1.3629604
## Criolla 0.4453887 0.6950155
## Sabanera -1.1990962 0.4487863
##
## $comparison
## NULL
##
## $groups
## Datos_papa$Indice_color groups
## Capiro 1.0483704 a
## Criolla 0.5954273 a
## Sabanera -0.5776758 a
##
## attr(,"class")
## [1] "group"Gravedad especifica
#Gravedad especifica
m5 <- aov(Gravedad_especifica~Trat, data = Datos_papa)
anova(m5)## Analysis of Variance Table
##
## Response: Gravedad_especifica
## Df Sum Sq Mean Sq F value Pr(>F)
## Trat 2 5510096 2755048 108.15 1.966e-05 ***
## Residuals 6 152844 25474
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1shapiro.test(resid(m5))##
## Shapiro-Wilk normality test
##
## data: resid(m5)
## W = 0.91682, p-value = 0.3666leveneTest(Datos_papa$Gravedad_especifica~Datos_papa$Trat, center=mean)## Warning in leveneTest.default(y = y, group = group, ...): group coerced to
## factor.## Levene's Test for Homogeneity of Variance (center = mean)
## Df F value Pr(>F)
## group 2 2.7864 0.1394
## 6m5Tukey <-HSD.test(Datos_papa$Gravedad_especifica, Datos_papa$Trat, 6, 25474, alpha = 0.05)
m5Tukey## $statistics
## MSerror Df Mean CV MSD
## 25474 6 1451.905 10.99285 399.85
##
## $parameters
## test name.t ntr StudentizedRange alpha
## Tukey Datos_papa$Trat 3 4.339195 0.05
##
## $means
## Datos_papa$Gravedad_especifica std r Min Max
## Capiro 2447.4849 233.3561 3 2180.8718 2614.6021
## Criolla 535.8272 102.2118 3 450.2717 649.0141
## Sabanera 1372.4025 107.3291 3 1289.1429 1493.5333
## Q25 Q50 Q75
## Capiro 2363.9262 2546.9807 2580.7914
## Criolla 479.2337 508.1957 578.6049
## Sabanera 1311.8371 1334.5313 1414.0323
##
## $comparison
## NULL
##
## $groups
## Datos_papa$Gravedad_especifica groups
## Capiro 2447.4849 a
## Sabanera 1372.4025 b
## Criolla 535.8272 c
##
## attr(,"class")
## [1] "group"m10LSD <- LSD.test(Datos_papa$Gravedad_especifica, Datos_papa$Trat, 6, 25474, alpha = 0.05)
m10LSD## $statistics
## MSerror Df Mean CV t.value LSD
## 25474 6 1451.905 10.99285 2.446912 318.8756
##
## $parameters
## test p.ajusted name.t ntr alpha
## Fisher-LSD none Datos_papa$Trat 3 0.05
##
## $means
## Datos_papa$Gravedad_especifica std r LCL UCL
## Capiro 2447.4849 233.3561 3 2222.0058 2672.9640
## Criolla 535.8272 102.2118 3 310.3481 761.3062
## Sabanera 1372.4025 107.3291 3 1146.9234 1597.8816
## Min Max Q25 Q50 Q75
## Capiro 2180.8718 2614.6021 2363.9262 2546.9807 2580.7914
## Criolla 450.2717 649.0141 479.2337 508.1957 578.6049
## Sabanera 1289.1429 1493.5333 1311.8371 1334.5313 1414.0323
##
## $comparison
## NULL
##
## $groups
## Datos_papa$Gravedad_especifica groups
## Capiro 2447.4849 a
## Sabanera 1372.4025 b
## Criolla 535.8272 c
##
## attr(,"class")
## [1] "group"