title: “A4Q2”

author: “sanjay”

date: “2026-04-12”

output: html_document

library(readxl)
library(ggpubr)

## Loading required package: ggplot2

DatasetZ <- read_excel("C:/Users/sanja/Downloads/A4Q2.xlsx")
ggscatter(
  DatasetZ,
  x = "phone",
  y = "sleep",
  add = "reg.line",
  xlab = "phone usage",
  ylab = "sleep"
)

mean(DatasetZ$phone)

## [1] 3.804609

sd(DatasetZ$phone)

## [1] 2.661866

median(DatasetZ$phone)

## [1] 3.270839

mean(DatasetZ$sleep)

## [1] 7.559076

sd(DatasetZ$sleep)

## [1] 1.208797

median(DatasetZ$sleep)

## [1] 7.524099

hist(DatasetZ$phone,
     main = "phone",
     breaks = 20,
     col = "lightblue",
     border = "white",
     cex.main = 1,
     cex.axis = 1,
     cex.lab = 1)

hist(DatasetZ$sleep,
     main = "sleep",
     breaks = 20,
     col = "lightcoral",
     border = "white",
     cex.main = 1,
     cex.axis = 1,
     cex.lab = 1)

# Variable 1: phone
# The first variable looks [abnormally] distributed.
# The data is [positively skewed].
# The data [does not have] a proper bell curve.
# Variable 2: sleep
# The first variable looks [abnormally] distributed.
# The data is [symmetrical / negatively skewed].
# The data [does not have] a proper bell curve.
shapiro.test(DatasetZ$phone)

## 
##  Shapiro-Wilk normality test
## 
## data:  DatasetZ$phone
## W = 0.89755, p-value = 9.641e-09

shapiro.test(DatasetZ$sleep)

## 
##  Shapiro-Wilk normality test
## 
## data:  DatasetZ$sleep
## W = 0.91407, p-value = 8.964e-08

# Variable 1: phone
# The first variable is [abnormally] distributed (p < .001).
# Variable 2: sleep
# The second variable is [abnormally] distributed (p < .001).
cor.test(DatasetZ$phone, DatasetZ$sleep, method = "spearman")

## 
##  Spearman's rank correlation rho
## 
## data:  DatasetZ$phone and DatasetZ$sleep
## S = 908390, p-value < 2.2e-16
## alternative hypothesis: true rho is not equal to 0
## sample estimates:
##        rho 
## -0.6149873

# A Spearman correlation was conducted to test the relationship between Variable 1 (Mdn = 3.27) and Variable 2 (Mdn = 7.52).
# There [was] a statistically significant relationship between the two variables, ρ = -.61, p < .001.
# The relationship was negative and strong.
# As the phone increased, the dependent sleep decreased.



# The relationship is [linear].
# The relationship is [negative].
# The relationship is [moderate to strong].
## There [are] outliers.