Assign 1, Q2

library(readxl)
library(ggpubr)

## Loading required package: ggplot2

phone <- read_excel("phone.xlsx")
library(ggpubr)

ggscatter(
  data = phone,
  x = "phone",
  y = "sleep",
  add = "reg.line",
  xlab = "Phone Use",
  ylab = "Sleep"
)

Scatterplot creation and intrpretation. The relationship is linear, negative, strong, with minor outliers. Data reflects negative linear relationship requiring pearson.

4. Descriptive Stats

mean(phone$phone)

## [1] 3.804609

sd(phone$phone)

## [1] 2.661866

median(phone$phone)

## [1] 3.270839

mean(phone$sleep)

## [1] 7.559076

sd(phone$sleep)

## [1] 1.208797

median(phone$sleep)

## [1] 7.524099

5. Normality

hist(phone$phone,
     main = "Phone Use",
     breaks = 20,
     col = "lightblue",
     border = "white",
     cex.main = 1,
     cex.axis = 1,
     cex.lab = 1)

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

Variable 1: Phone use. The first variable appears abnormally distributed. The data appears postively skewed. The data does not have a proper bell curve.

Variable 2: sleep The first variable looks abnormally distributed. The data is negatively skewed.The data does not have a proper bell curve.

7. Shapiro test

shapiro.test(phone$phone)

## 
##  Shapiro-Wilk normality test
## 
## data:  phone$phone
## W = 0.89755, p-value = 9.641e-09

shapiro.test(phone$sleep)

## 
##  Shapiro-Wilk normality test
## 
## data:  phone$sleep
## W = 0.91407, p-value = 8.964e-08

Variable 1: Phone use. The first variable is abnormally distributed (p = .90) Variable 2: Sleep. The second variable is abnormally distributed. (p = .91)

9. Normality determined. Both historgrams are not normal and SW tests are not nomral.

10. Use Spearman.

cor.test(phone$phone, phone$sleep, method = "spearman")

## 
##  Spearman's rank correlation rho
## 
## data:  phone$phone and phone$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, p < .001, p < .001. The relationship was negative] and strong.

As the phone use increased, sleep decreased.