’’’{r}

library(readxl)

’’’

’’’{r}

library(ggpubr)

’’’

’’’{r}

A4Q2 <- read_excel(“Desktop/A4Q2.xlsx”)

’’’

’’’{r}

View(A4Q2)

’’’

’’’{r}

ggscatter(A4Q2,x=“phone”,y=“sleep”,add=“reg.line”,xlab=“Phone”,ylab=“Sleep”)

’’’

The relationship is linear. The relationship is negative. The relationship is weak to moderate. There are outliers.

’’’{r}

mean(A4Q2$phone)

’’’

[1] 3.804609

’’’{r}

sd(A4Q2$phone)

’’’

[1] 2.661866

’’’{r}

median(A4Q2$phone)

’’’

[1] 3.270839

’’’{r}

mean(A4Q2$sleep)

’’’

[1] 7.559076

’’’{r}

sd(A4Q2$sleep)

’’’

[1] 1.208797

’’’{r}

median(A4Q2$sleep)

’’’ [1] 7.524099

’’’{r}

hist(A4Q2$phone,main=“Phone”,breaks=20,col=“blue”,border=“white”,cex.main=1,cex.axis=1,cex.lab=1)

’’’

’’’{r}

hist(A4Q2$sleep,main=“Sleep”,breaks=20,col=“red”,border=“white”,cex.main=1,cex.axis=1,cex.lab=1)

’’’

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

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

’’’{r}

shapiro.test(A4Q2$phone)

’’’

Shapiro-Wilk normality test

data: A4Q2$phone W = 0.89755, p-value = 9.641e-09

’’’{r}

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 = 9.641e-09)

Variable 2: Sleep The second variable is abnormally distributed (p = 8.964e-08)

’’’{r}

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 person’s phone usage in hours (Mdn = 3.27) and sleep in hours (Mdn = 7.52). There was a statistically significant relationship between the two variables, rho = -.61, p < .001. The relationship was negative and strong. As phone usage increased, sleep decreased.