Load Library dan Import Dataset

library(readxl)
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
library(DescTools)
## Warning: package 'DescTools' was built under R version 4.0.3
data <- read_xls("D:/DataCompetition/RASIO/data.xls")

Five-Number Summary

summary(data$QoL0)
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##    40.0    52.0    57.0    59.1    64.0    96.0

Split Data Berdasarkan Kategori Treatment

A <- data %>% filter(Treat=="A")
AB <- data %>% filter(Treat=="AB")
A
## # A tibble: 34 x 6
##    id    Treat  QoL0  QoL1  QoL2  QoL3
##    <chr> <chr> <dbl> <dbl> <dbl> <dbl>
##  1 r01   A        72    94    67   100
##  2 r02   A        48    54    63    68
##  3 r03   A        58    72    69    78
##  4 r04   A        54    91    92    95
##  5 r05   A        60   100   100   100
##  6 r06   A        65    80    83    82
##  7 r07   A        62    79    78    72
##  8 r08   A        45    98    96    93
##  9 r09   A        50    91    92    88
## 10 r10   A        57    98   100   100
## # ... with 24 more rows
AB
## # A tibble: 35 x 6
##    id    Treat  QoL0  QoL1  QoL2  QoL3
##    <chr> <chr> <dbl> <dbl> <dbl> <dbl>
##  1 r35   AB       59    69    80    82
##  2 r36   AB       67    97    96    97
##  3 r37   AB       45    94    95    95
##  4 r38   AB       52    75    87    72
##  5 r39   AB       49    94    93    95
##  6 r40   AB       40   100    99    94
##  7 r41   AB       61    99    98   100
##  8 r42   AB       51    91    94    96
##  9 r43   AB       57    84    83    82
## 10 r44   AB       64    99    98    93
## # ... with 25 more rows

Uji Normalitas

shapiro.test(data$QoL0)
## 
##  Shapiro-Wilk normality test
## 
## data:  data$QoL0
## W = 0.93307, p-value = 0.00114

Point A

Aframe <- data.frame(A)
wilcox.test(Aframe$QoL0,Aframe$QoL1,paired=TRUE,alternative="less")
## Warning in wilcox.test.default(Aframe$QoL0, Aframe$QoL1, paired = TRUE, : cannot
## compute exact p-value with ties
## 
##  Wilcoxon signed rank test with continuity correction
## 
## data:  Aframe$QoL0 and Aframe$QoL1
## V = 13, p-value = 5.985e-07
## alternative hypothesis: true location shift is less than 0

Point B

ABframe <- data.frame(AB)
wilcox.test(Aframe$QoL1,ABframe$QoL1,paired=F,alternative="less")
## Warning in wilcox.test.default(Aframe$QoL1, ABframe$QoL1, paired = F,
## alternative = "less"): cannot compute exact p-value with ties
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Aframe$QoL1 and ABframe$QoL1
## W = 510.5, p-value = 0.1563
## alternative hypothesis: true location shift is less than 0

Point C

pejA <- as.matrix(data.frame(A$QoL0,A$QoL1,A$QoL2,A$QoL3))
PageTest(pejA)
## 
##  Page test for ordered alternatives
## 
## data:  pejA
## L = 960, p-value = 1.476e-12