A6Q2

library(readxl)
library(ggpubr)

## Loading required package: ggplot2

library(effsize)
library(rstatix)

## 
## Attaching package: 'rstatix'

## The following object is masked from 'package:stats':
## 
##     filter

library(readxl)
A6Q2 <- read_excel("C:/Users/edavi/OneDrive/Desktop/A6Q2.xlsx")
View(A6Q2)

Before<-A6Q2$Before
After<-A6Q2$After
Differences<-After-Before

mean(Before,na.rm=TRUE)

## [1] 76.13299

[1] 76.13299

median(Before,na.rm=TRUE)

## [1] 75.95988

[1] 75.95988

sd(Before,na.rm=TRUE)

## [1] 7.781323

[1] 7.781323

mean(After,na.rm=TRUE)

## [1] 57.17874

[1] 57.17874

median(After,na.rm=TRUE)

## [1] 58.36459

[1] 58.36459

sd(After,na.rm=TRUE)

## [1] 14.39364

[1] 14.39364

hist(Differences,main="Histogram of Difference Scores",xlab="Value",ylab="Frequency",col="blue",border="black",breaks=20)

Histogram of Difference Scores The difference scores look abnormally distributed. The data is negatively skewed. The data does not have a proper bell curve.

boxplot(Differences,main="Distribution of Score Differences (After - Before)",ylab="Difference in Scores",col="blue",border="darkblue")

Boxplot There is one dot outside the boxplot. The dot is not close to the whiskers. The dot is very far away from the whiskers. Based on these findings, the boxplot is not normal.

shapiro.test(Differences)

## 
##  Shapiro-Wilk normality test
## 
## data:  Differences
## W = 0.89142, p-value = 0.02856

Shapiro-Wilk normality test

data: Differences W = 0.89142, p-value = 0.02856

Shapiro-Wilk Difference Scores The data is abnormally distributed, (p = .029)

wilcox.test(Before,After,paired=TRUE,na.action=na.omit)

## 
##  Wilcoxon signed rank exact test
## 
## data:  Before and After
## V = 210, p-value = 1.907e-06
## alternative hypothesis: true location shift is not equal to 0

Wilcoxon signed rank exact test

data: Before and After V = 210, p-value = 1.907e-06 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   0.877    20    20 large

A tibble: 1 × 7 .y. group1 group2 effsize n1 n2 magnitude *
1 score After Before 0.877 20 20 large

A Wilcoxon Signed-Rank Test was conducted to determine if there was a difference in Body Weight (kg) before the keto diet versus after the keto diet. Before scores (Mdn = 75.96) were significantly different from after scores (Mdn = 58.36), V = 210, p < .001. The effective size was large, r = .88.