library(readxl)
library(ggpubr)
## Loading required package: ggplot2
library(rmarkdown)
ds2 <- read_excel("~/Downloads/ds2.xlsx")
ggscatter(
     ds2,
     x = "phone",
     y = "sleep",
     add = "reg.line",
     xlab = "Phone (hours)",
     ylab = "Sleep (hours)"
     
)

mean(ds2$phone)
## [1] 3.804609
sd(ds2$phone)
## [1] 2.661866
median(ds2$phone)
## [1] 3.270839
mean(ds2$sleep)
## [1] 7.559076
sd(ds2$sleep)
## [1] 1.208797
median(ds2$sleep)
## [1] 7.524099
hist(ds2$phone,
      main = "Phone (hours)",
      breaks = 20,
      col = "lightblue",
      border = "white",
      cex.main = 1,
      cex.axis = 1,
      cex.lab = 1)

hist(ds2$sleep,
      main = "Sleep (hours)",
      breaks = 20,
      col = "lightcoral",
      border = "white",
      cex.main = 1,
      cex.axis = 1,
      cex.lab = 1)

Phone is abnormally distributed. The data is positively skewed. The data does not have a proper bell curve. Sleep is abnormally distributed. The data is negatively skewed. The data has a proper bell curve.

shapiro.test(ds2$phone)
## 
##  Shapiro-Wilk normality test
## 
## data:  ds2$phone
## W = 0.89755, p-value = 9.641e-09
shapiro.test(ds2$sleep)
## 
##  Shapiro-Wilk normality test
## 
## data:  ds2$sleep
## W = 0.91407, p-value = 8.964e-08

Phone is abnormal. Sleep is abnormal.

cor.test(ds2$phone,ds2$sleep,method="spearman")
## 
##  Spearman's rank correlation rho
## 
## data:  ds2$phone and ds2$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 phone use (Mdn = 3.27) and sleep (Mdn = 7.52). There was a statistically significant relationship between the two variables, ρ = -.65, p < .001. The relationship was negative and strong. As phone use increased, sleep decreased.