A6Q2

install.packages(“rstatix”) install.packages(“effectsize”)

library(readxl)

## Warning: package 'readxl' was built under R version 4.4.3

library(ggpubr)

## Warning: package 'ggpubr' was built under R version 4.4.3

## Loading required package: ggplot2

## Warning: package 'ggplot2' was built under R version 4.4.3

library(effectsize)

## Warning: package 'effectsize' was built under R version 4.4.3

library(rstatix)

## Warning: package 'rstatix' was built under R version 4.4.3

## 
## Attaching package: 'rstatix'

## The following objects are masked from 'package:effectsize':
## 
##     cohens_d, eta_squared

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

A6Q1 <- read_excel("C:/Users/vinay_17rmu0l/Downloads/A6Q2.xlsx")

Before <- (A6Q1$Before)
After <- (A6Q1$After)

Differences <- After - Before
mean(Before, na.rm = TRUE)

## [1] 76.13299

median(Before, na.rm = TRUE)

## [1] 75.95988

sd(Before, na.rm = TRUE)

## [1] 7.781323

mean(After, na.rm = TRUE)

## [1] 57.17874

median(After, na.rm = TRUE)

## [1] 58.36459

sd(After, na.rm = TRUE)

## [1] 14.39364

hist(Differences,
     main = "Histogram of Weight Change After Keto Diet",
     xlab = "Weight Change (kg) [After − Before]",
     ylab = "Number of Participants",
     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 = "Weight Difference (kg)",
        col = "blue",
        border = "darkblue")

Boxplot There [are] dots outside the boxplot. The dots [are not] close to the whiskers. The dots [are] very far away from the whiskers. Based on these findings, the boxplot is [normal]

shapiro.test(Differences)

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

Shapiro-Wilk Difference Scores The data is [abnormally] distributed, (p = 0.02856).

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

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 Wilcoxon Signed-Rank Test was conducted to determine if there was a difference in OutcomeVariable before Independent Variable versus after Independent Variable. Before scores (Mdn = 75.96) were [significantly] different from after scores (Mdn = 58.36), V = 210, p < .001. The effect size was [large], r = 0.877.