library(readxl)
library(effectsize)
library(rstatix)
## 
## Attaching package: 'rstatix'
## The following objects are masked from 'package:effectsize':
## 
##     cohens_d, eta_squared
## The following object is masked from 'package:stats':
## 
##     filter
Dataset6_4 <- read_excel("C:/Users/Mrlaz/Downloads/Dataset6.4.xlsx")

Before <- Dataset6_4$Stress_Pre
After  <- Dataset6_4$Stress_Post

Differences <- After - Before

mean(Before); median(Before); sd(Before)
## [1] 51.53601
## [1] 47.24008
## [1] 17.21906
mean(After); median(After); sd(After)
## [1] 41.4913
## [1] 40.84836
## [1] 18.88901
hist(Differences, col="blue")

boxplot(Differences, col="blue")

shapiro.test(Differences)
## 
##  Shapiro-Wilk normality test
## 
## data:  Differences
## W = 0.87495, p-value = 0.0008963
t.test(Before, After, paired=TRUE)
## 
##  Paired t-test
## 
## data:  Before and After
## t = 6.2067, df = 34, p-value = 4.649e-07
## alternative hypothesis: true mean difference is not equal to 0
## 95 percent confidence interval:
##   6.755787 13.333620
## sample estimates:
## mean difference 
##         10.0447
wilcox.test(Before, After, paired=TRUE)
## 
##  Wilcoxon signed rank exact test
## 
## data:  Before and After
## V = 620, p-value = 2.503e-09
## alternative hypothesis: true location shift is not equal to 0
df_long <- data.frame(
  id=rep(1:length(Before),2),
  time=rep(c("Before","After"),each=length(Before)),
  score=c(Before,After)
)

wilcox_effsize(df_long, score~time, paired=TRUE)
## # A tibble: 1 × 7
##   .y.   group1 group2 effsize    n1    n2 magnitude
## * <chr> <chr>  <chr>    <dbl> <int> <int> <ord>    
## 1 score After  Before   0.844    35    35 large

Difference normality p = 0.0009 → NOT normal Use Wilcoxon Signed Rank Medians Before ≈ 47.84 After ≈ 40.94 Significance p < .001

There was a significant reduction in stress levels between before the exercise program (Mdn = 47.84) and after the program (Mdn = 40.94), p < .001.