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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 (readxl)
library (car) 

## Zorunlu paket yükleniyor: carData

## 
## Attaching package: 'car'

## The following object is masked from 'package:dplyr':
## 
##     recode

library(effectsize) 

anova_data <- read_excel("C:/Users/melik/Downloads/anova_dataset.xlsx")

head(anova_data) 

## # A tibble: 6 × 3
##   participant_id group       anxiety_score
##   <chr>          <chr>               <dbl>
## 1 MIN_001        Mindfulness          52.0
## 2 MIN_002        Mindfulness          46.9
## 3 MIN_003        Mindfulness          53.2
## 4 MIN_004        Mindfulness          60.2
## 5 MIN_005        Mindfulness          46.1
## 6 MIN_006        Mindfulness          46.1

anova_data$group <- as.factor(anova_data$group)
glimpse (anova_data) 

## Rows: 277
## Columns: 3
## $ participant_id <chr> "MIN_001", "MIN_002", "MIN_003", "MIN_004", "MIN_005", …
## $ group          <fct> Mindfulness, Mindfulness, Mindfulness, Mindfulness, Min…
## $ anxiety_score  <dbl> 51.97, 46.89, 53.18, 60.18, 46.13, 46.13, 60.63, 54.14,…

table(anova_data$group)

## 
##     Control    Exercise Mindfulness 
##          90          95          92

by(anova_data$anxiety_score,
   anova_data$group,
   shapiro.test)

## anova_data$group: Control
## 
##  Shapiro-Wilk normality test
## 
## data:  dd[x, ]
## W = 0.99129, p-value = 0.8211
## 
## ------------------------------------------------------------ 
## anova_data$group: Exercise
## 
##  Shapiro-Wilk normality test
## 
## data:  dd[x, ]
## W = 0.98017, p-value = 0.1597
## 
## ------------------------------------------------------------ 
## anova_data$group: Mindfulness
## 
##  Shapiro-Wilk normality test
## 
## data:  dd[x, ]
## W = 0.98912, p-value = 0.652

leveneTest(anxiety_score ~ group, data = anova_data)

## Levene's Test for Homogeneity of Variance (center = median)
##        Df F value Pr(>F)
## group   2  0.8155 0.4435
##       274

anova_model <- aov(anxiety_score ~ group, data = anova_data)
summary(anova_model)

##              Df Sum Sq Mean Sq F value Pr(>F)    
## group         2   5119  2559.7   41.61 <2e-16 ***
## Residuals   274  16856    61.5                   
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

TukeyHSD(anova_model) 

##   Tukey multiple comparisons of means
##     95% family-wise confidence level
## 
## Fit: aov(formula = anxiety_score ~ group, data = anova_data)
## 
## $group
##                            diff        lwr       upr     p adj
## Exercise-Control      -4.551064  -7.269890 -1.832238 0.0002986
## Mindfulness-Control  -10.567418 -13.307724 -7.827111 0.0000000
## Mindfulness-Exercise  -6.016354  -8.719961 -3.312746 0.0000009

eta_squared(anova_model, partial = FALSE)

## # Effect Size for ANOVA (Type I)
## 
## Parameter | Eta2 |       95% CI
## -------------------------------
## group     | 0.23 | [0.16, 1.00]
## 
## - One-sided CIs: upper bound fixed at [1.00].

Sonuç; Tek yönlü ANOVA sonucunda üç grubun sınav kaygısı puanları arasında anlamlı fark bulunmuştur. Çoklu karşılaştırmalar, mindfulness grubunun en düşük sınav kaygısına sahip olduğunu göstermiştir. Grup etkisinin büyüklüğü η² = 0.23 olarak bulunmuştur.