#mann whitney u testi:

library(tidyverse)
## Warning: package 'tidyverse' was built under R version 4.5.3
## Warning: package 'ggplot2' was built under R version 4.5.2
## Warning: package 'tidyr' was built under R version 4.5.2
## Warning: package 'readr' was built under R version 4.5.3
## Warning: package 'purrr' was built under R version 4.5.2
## Warning: package 'dplyr' was built under R version 4.5.2
## Warning: package 'stringr' was built under R version 4.5.2
## Warning: package 'forcats' was built under R version 4.5.3
## Warning: package 'lubridate' was built under R version 4.5.3
## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr     1.1.4     ✔ readr     2.2.0
## ✔ forcats   1.0.1     ✔ stringr   1.6.0
## ✔ ggplot2   4.0.1     ✔ tibble    3.3.0
## ✔ lubridate 1.9.5     ✔ tidyr     1.3.2
## ✔ purrr     1.2.0     
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag()    masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
library(lsr) #mann-whitney etki büyüklüğü için.
## Warning: package 'lsr' was built under R version 4.5.3
library(broom) #test çıktısını tabloya çevirmek için kullandık
## Warning: package 'broom' was built under R version 4.5.2
library(ggplot2) #görselleştirmek için kullandık.

iki grup için örnek veri (öğrencilerin stres puanları)

egzersiz_yapan <- c(18, 20, 22, 19, 17, 21, 23, 20)
egzersiz_yapmayan <- c(25, 28, 30, 27, 26, 29, 31, 28)
stres <- c(egzersiz_yapan, egzersiz_yapmayan)
grup <- factor(c(rep("yapan", length(egzersiz_yapan)), 
rep("yapmayan", 
    length(egzersiz_yapmayan))))
egzersiz_veri <- data.frame(grup, stres)
egzersiz_veri
##        grup stres
## 1     yapan    18
## 2     yapan    20
## 3     yapan    22
## 4     yapan    19
## 5     yapan    17
## 6     yapan    21
## 7     yapan    23
## 8     yapan    20
## 9  yapmayan    25
## 10 yapmayan    28
## 11 yapmayan    30
## 12 yapmayan    27
## 13 yapmayan    26
## 14 yapmayan    29
## 15 yapmayan    31
## 16 yapmayan    28
sonuc_egzersiz <- wilcox.test(stres ~ grup, data = egzersiz_veri)
## Warning in wilcox.test.default(x = DATA[[1L]], y = DATA[[2L]], ...): cannot
## compute exact p-value with ties
sonuc_egzersiz
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  stres by grup
## W = 0, p-value = 0.0009229
## alternative hypothesis: true location shift is not equal to 0
wilcox.test(egzersiz_yapan, egzersiz_yapmayan)
## Warning in wilcox.test.default(egzersiz_yapan, egzersiz_yapmayan): cannot
## compute exact p-value with ties
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  egzersiz_yapan and egzersiz_yapmayan
## W = 0, p-value = 0.0009229
## alternative hypothesis: true location shift is not equal to 0

#Egzersiz yapan ve yapmayan öğrencilerin stres düzeyleri arasında anlamlı bir fark bulunmuştur. (w= 0, p < .001).