library(readxl)
library(ggpubr)
## Loading required package: ggplot2
A4Q2 <- read_excel("C:/Users/laksh/Desktop/r studio/A4Q2.xlsx")
ggscatter(
  A4Q2,
  x = "sleep",
  y = "phone",
  add = "reg.line",
  xlab = "sleep",
  ylab = "phone"
)

The relationship is linear. The relationship is negative. The relationship is moderate or strong. There are no outliers

mean(A4Q2$sleep)
## [1] 7.559076
sd(A4Q2$sleep)
## [1] 1.208797
median(A4Q2$sleep)
## [1] 7.524099

calculating mean, median and deviation for variable 1

mean(A4Q2$phone)
## [1] 3.804609
sd(A4Q2$phone)
## [1] 2.661866
median(A4Q2$phone)
## [1] 3.270839

calculating mean, median and deviation for variable 2

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

Variable 1: Sleep The first variable looks abnormally distributed. The data is negatively skewed. The data does not have a proper bell curve.

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

Variable 2: Phone The second variable phone looks abnormally distributed. The data is positively skewed. The data does not have a proper bell curve.

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

Variable 1: sleep The first variable is abnormally distributed (p<.05).

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

Variable 2: phone The second variable is abnormally distributed (p<.05).

cor.test(A4Q2$sleep, A4Q2$phone, method = "spearman")
## 
##  Spearman's rank correlation rho
## 
## data:  A4Q2$sleep and A4Q2$phone
## 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 phone (Mdn = 7.52) and hours of sleep (Mdn = 3.27). There was a statistically significant relationship between the two variables, ρ = -0.61, p <0.001 The relationship was negative and strong. As usage of phone increased ,hours of sleep is decreased.