`

library(readxl)
golf <- read_excel("C:/Users/win10/Desktop/lab4 DBCA/golf.xlsx")
View(golf)
attach(golf)  ### no se necesita usar el $ para llamar variables
golf
## # A tibble: 20 x 3
##    cesped        terreno distancia
##    <chr>         <chr>       <dbl>
##  1 AgrTenuis(1)  B1            1.3
##  2 AgrCanina(2)  B2            2.2
##  3 Pasnotatum(3) B3            1.8
##  4 Vaginatum(4)  B4            3.9
##  5 AgrTenuis(1)  B1            1.6
##  6 AgrCanina(2)  B2            2.4
##  7 Pasnotatum(3) B3            1.7
##  8 Vaginatum(4)  B4            4.4
##  9 AgrTenuis(1)  B1            0.5
## 10 AgrCanina(2)  B2            0.4
## 11 Pasnotatum(3) B3            0.6
## 12 Vaginatum(4)  B4            2  
## 13 AgrTenuis(1)  B1            1.2
## 14 AgrCanina(2)  B2            2  
## 15 Pasnotatum(3) B3            1.5
## 16 Vaginatum(4)  B4            4.1
## 17 AgrTenuis(1)  B1            1.1
## 18 AgrCanina(2)  B2            1.8
## 19 Pasnotatum(3) B3            1.3
## 20 Vaginatum(4)  B4            3.4
TRATAMIENTO <- as.factor(cesped)
PATOLOGIA <- as.factor(terreno)

summary(cesped)
##    Length     Class      Mode 
##        20 character character
summary(terreno)
##    Length     Class      Mode 
##        20 character character

TRATAMIENTOS

library("ggplot2")
ggplot(golf, aes(x = cesped, y = distancia)) +
  geom_boxplot(fill = "grey80", colour = "blue") +
  scale_x_discrete() + xlab("Cesped") +
  ylab("Distancias")

BLOQUES

library("ggplot2")
ggplot(golf, aes(x = terreno, y = distancia)) +
  geom_boxplot(fill = "grey80", colour = "blue") +
  scale_x_discrete() + xlab("Terrenos") +
  ylab("Distancias")

anova Supuestos

anova.golf = aov(distancia ~ cesped+terreno, data=golf)
e<-anova.golf$residuals           ##### residuales

Normalidad si p_valor es mayor a 0,05 se cumple el supuesto.

se verifica si suma de residuales es igual a cero

t.test(e,mu=0)
## 
##  One Sample t-test
## 
## data:  e
## t = 1.1996e-16, df = 19, p-value = 1
## alternative hypothesis: true mean is not equal to 0
## 95 percent confidence interval:
##  -0.2968539  0.2968539
## sample estimates:
##    mean of x 
## 1.701384e-17
shapiro.test(e)          #### prueba Normalidad
## 
##  Shapiro-Wilk normality test
## 
## data:  e
## W = 0.87137, p-value = 0.01242
hist(e, freq=FALSE)
curve(dnorm(x,mean(e), sd(e)), xlim=c(-3,3), add=TRUE, col=2)

Homogeneidad de varianza ,si p_valor es mayaor se cumple

library(carData)
library(car)
leveneTest(e ~ as.factor(cesped), data =golf, center = "median") #####homogeneidad
## Levene's Test for Homogeneity of Variance (center = "median")
##       Df F value Pr(>F)
## group  3  0.4517 0.7197
##       16

Independencia .prueba de rachas, si pvalor sale mayor a 0,05 se cumple

library(randtests)
runs.test(e)
## 
##  Runs Test
## 
## data:  e
## statistic = -2.2973, runs = 6, n1 = 10, n2 = 10, n = 20, p-value =
## 0.0216
## alternative hypothesis: nonrandomness

ANOVA DBCA

anova.golf = aov(distancia ~ cesped+terreno, data=golf)
summary(anova.golf)
##             Df Sum Sq Mean Sq F value   Pr(>F)    
## cesped       3 18.044   6.015   12.59 0.000176 ***
## Residuals   16  7.644   0.478                     
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

post anova

library(agricolae) #### PAQUETE DE PRUEBAS POST-ANOVA
##### PRUEBA TUKEY
HSD.test(anova.golf,"cesped", alpha=0.05, console=TRUE, group=FALSE)
## 
## Study: anova.golf ~ "cesped"
## 
## HSD Test for distancia 
## 
## Mean Square Error:  0.47775 
## 
## cesped,  means
## 
##               distancia       std r Min Max
## AgrCanina(2)       1.76 0.7924645 5 0.4 2.4
## AgrTenuis(1)       1.14 0.4037326 5 0.5 1.6
## Pasnotatum(3)      1.38 0.4764452 5 0.6 1.8
## Vaginatum(4)       3.56 0.9449868 5 2.0 4.4
## 
## Alpha: 0.05 ; DF Error: 16 
## Critical Value of Studentized Range: 4.046093 
## 
## Comparison between treatments means
## 
##                              difference pvalue signif.        LCL        UCL
## AgrCanina(2) - AgrTenuis(1)        0.62 0.5066         -0.6306944  1.8706944
## AgrCanina(2) - Pasnotatum(3)       0.38 0.8205         -0.8706944  1.6306944
## AgrCanina(2) - Vaginatum(4)       -1.80 0.0040      ** -3.0506944 -0.5493056
## AgrTenuis(1) - Pasnotatum(3)      -0.24 0.9455         -1.4906944  1.0106944
## AgrTenuis(1) - Vaginatum(4)       -2.42 0.0002     *** -3.6706944 -1.1693056
## Pasnotatum(3) - Vaginatum(4)      -2.18 0.0007     *** -3.4306944 -0.9293056

prueba LSD

LSD.test(anova.golf,"cesped",console=TRUE)
## 
## Study: anova.golf ~ "cesped"
## 
## LSD t Test for distancia 
## 
## Mean Square Error:  0.47775 
## 
## cesped,  means and individual ( 95 %) CI
## 
##               distancia       std r       LCL      UCL Min Max
## AgrCanina(2)       1.76 0.7924645 5 1.1047126 2.415287 0.4 2.4
## AgrTenuis(1)       1.14 0.4037326 5 0.4847126 1.795287 0.5 1.6
## Pasnotatum(3)      1.38 0.4764452 5 0.7247126 2.035287 0.6 1.8
## Vaginatum(4)       3.56 0.9449868 5 2.9047126 4.215287 2.0 4.4
## 
## Alpha: 0.05 ; DF Error: 16
## Critical Value of t: 2.119905 
## 
## least Significant Difference: 0.9267163 
## 
## Treatments with the same letter are not significantly different.
## 
##               distancia groups
## Vaginatum(4)       3.56      a
## AgrCanina(2)       1.76      b
## Pasnotatum(3)      1.38      b
## AgrTenuis(1)       1.14      b
kruskal.test(e ~ as.factor(cesped), data =golf)
## 
##  Kruskal-Wallis rank sum test
## 
## data:  e by as.factor(cesped)
## Kruskal-Wallis chi-squared = 0.57714, df = 3, p-value = 0.9016