ASSIGN 4 Q 2

library(readxl)

## Warning: package 'readxl' was built under R version 4.5.3

library(ggpubr)

## Warning: package 'ggpubr' was built under R version 4.5.3

## Loading required package: ggplot2

## Warning: package 'ggplot2' was built under R version 4.5.3

A4Q2 <- read_excel("C:/Users/jrutebuka/Desktop/A4Q2.xlsx")

ggscatter(
    A4Q2,
    x = "phone",
    y = "sleep",
    add = "reg.line",
    xlab = "phone",
    ylab = "sleep"
  )

# The relationship is linear.

# The relationship is negative.

# The relationship is moderate.

# There are outliers

mean(A4Q2$phone)

## [1] 3.804609

sd(A4Q2$phone)

## [1] 2.661866

median(A4Q2$phone)

## [1] 3.270839

mean(A4Q2$sleep)

## [1] 7.559076

sd(A4Q2$sleep)

## [1] 1.208797

median(A4Q2$sleep)

## [1] 7.524099

hist(A4Q2$phone,
     main = "phone",
     breaks = 20,
     col = "lightblue",
     border = "white",
     cex.main = 1,
     cex.axis = 1,
     cex.lab = 1)

hist(A4Q2$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 normally distributed.
# The data is symmetrical.
# The data has a proper bell curve.
# Variable 1: sleep
# The first variable looks normally distributed.
# The data is symmetrical.
# The data has a proper bell curve.

shapiro.test(A4Q2$phone)

## 
##  Shapiro-Wilk normality test
## 
## data:  A4Q2$phone
## W = 0.89755, p-value = 9.641e-09

shapiro.test(A4Q2$sleep)

## 
##  Shapiro-Wilk normality test
## 
## data:  A4Q2$sleep
## W = 0.91407, p-value = 8.964e-08

# Variable 1: phone
# The first variable is normally distributed (p =9.641e-09).
# Variable 2: sleep
# The second variable is normally distributed (p =8.964e-08).

cor.test(A4Q2$phone, A4Q2$sleep, method = "spearman")

## 
##  Spearman's rank correlation rho
## 
## data:  A4Q2$phone and A4Q2$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 the hours of sleep (Mdn = 7.52) and the hours of phone use (Mdn = 3.27).
# There was a statistically significant relationship between the two variables, ρ < 0.001, p <0.001.
# The relationship was negative and moderate.
# As the hours of sleep increased, the hours of phone use decrease.