install.packages(“readxl”) install.packages(“ggpubr”)

library(readxl)
library(ggpubr)
## Loading required package: ggplot2
A4Q2 <- read_excel("C:/Users/nbodi/OneDrive/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 no 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 abnormally distributed. The data does not have a proper bell curve.

Variable 2: sleep The second variable looks abnormally distributed. The data is symmetrical/ negatively skewed The data does not have 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 abnormally distributed (p <.001). Variable 2: sleep The second variable is abnormally distributed (p <.001).

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 a 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 phone increased, the dependent sleep decreased.