The relationship is linear.

The relationship is negative.

The relationship is strong.

There are no outliers.

mean(A4Q2$sleep)
## [1] 7.559076
sd(A4Q2$sleep)
## [1] 1.208797
median(A4Q2$sleep)
## [1] 7.524099
mean(A4Q2$phone)
## [1] 3.804609
sd(A4Q2$phone)
## [1] 2.661866
median(A4Q2$phone)
## [1] 3.270839
hist(A4Q2$sleep,
     main = "sleep",
     breaks = 20,
     col = "lightblue",
     border = "white",
     cex.main = 1,
     cex.axis = 1,
     cex.lab = 1)

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

Variable 1: sleep The first variable does not looks normally distributed. The data is not symmetrical. The data has no proper bell curve.

Variable 2: phone The second variable does not looks normally distributed. The data is not symmetrical. The data has no proper bell curve.

shapiro.test(A4Q2$sleep)
## 
##  Shapiro-Wilk normality test
## 
## data:  A4Q2$sleep
## W = 0.91407, p-value = 8.964e-08
shapiro.test(A4Q2$phone)
## 
##  Shapiro-Wilk normality test
## 
## data:  A4Q2$phone
## W = 0.89755, p-value = 9.641e-09

Variable 1: sleep The first variable is not normally distributed (p = 8.964e-08).

Variable 2: phone The second variable is not normally distributed (p = 9.641e-09).

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 sleep (Mdn = 7.524) and phone (Mdn = 3.270). There was a statistically significant relationship between the two variables, ρ = -0.615, p = 2.2e-16. The relationship was negative and strong . As sleep increased, phone decreases.