CORRECTION: Insert Question

Is there a difference in body weight (kg) before versus after all participants tried the keto diet?

CORRECTION: Clutter noted in packages. Searched to find correct to remove per below.

Open Packages.

library(readxl)
library(ggpubr)
library(dplyr)
library(effectsize)
library(effsize)
library(ggplot2)
library(rstatix)

CORRECTION - Indicate step. Import Data set.

A6Q2 <- read_excel("C:/Users/rmich/Desktop/A6Q2.xlsx")

CORRECTION - Indicate step. Create before and after variables.

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

CORRECTION - Indicate Step. Calcualte before and afters.

Differences <- After - Before

CORRECTION - Indicate step. Descriptive statistics.

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 - Before and After Keto",
     xlab = "Weight",
     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 of Weight - Before and After Keto",
        ylab = "Difference in Weight",
        col = "blue",
        border = "darkblue")

#Boxplot #There is a 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.

CORRECTION: Indicate Step - Check normality.

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

Interpretation: 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

CORRECTION: Remove T Test. CORRECTION: Remove COhen D.

Effect Size:

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

CORRECTION - Remove dependent t test info.

A Wilcoxon Signed-Rank Test was conducted to determine if there was a difference in Weight before Keto and after Keto. Weight before (Mdn = 75.96) were significantly different from weight after (Mdn = 58.36), V = 210, p = < .001. The effect size was large, r = .88