library(readxl)
library(ggpubr)
## Loading required package: ggplot2
library(effectsize)
library(rstatix)
## 
## 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/sunde/OneDrive/Desktop/A6Q1.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] 71.58994
median(After, na.rm = TRUE)
## [1] 70.88045
sd(After, na.rm = TRUE)
## [1] 6.639509
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 negetively skewed.
#The data has a no 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 close to the whiskers.
#The dot is not very far away from the whiskers.
#Based on these findings, the boxplot is normal.

shapiro.test(Differences)
## 
##  Shapiro-Wilk normality test
## 
## data:  Differences
## W = 0.94757, p-value = 0.3318
#Shapiro-Wilk Difference Scores
#The data is normally distributed, (p >.05).

t.test(Before, After, paired = TRUE, na.action = na.omit)
## 
##  Paired t-test
## 
## data:  Before and After
## t = 1.902, df = 19, p-value = 0.07245
## alternative hypothesis: true mean difference is not equal to 0
## 95 percent confidence interval:
##  -0.4563808  9.5424763
## sample estimates:
## mean difference 
##        4.543048
#A Dependent T-Test was conducted to determine if there was a difference in weight before the diet versus after the diet.
#Before scores (M = 76.13, SD = 6.63) were significantly different from after scores (M = 71.58, SD = 6.63), t(19) = 1.90, p >0.05.