A5 Q2

What are the null and alternate hypotheses for your research?

H0:There is no relationship between the number of laptops purchased and the number of antivirus licenses purchased

H1:There is a relationship between the number of laptops purchased and the number of antivirus licenses purchased

library(readxl)

A5RQ2 <- read_excel("C:\\Users\\kuppi\\OneDrive\\Desktop\\A5RQ2.xlsx")

library(psych)

describe(A5RQ2[, c("Antivirus", "Laptop")])

##           vars   n  mean    sd median trimmed   mad min max range  skew
## Antivirus    1 122 50.18 13.36     49   49.92 12.60  15  83    68  0.15
## Laptop       2 122 40.02 12.30     39   39.93 11.86   8  68    60 -0.01
##           kurtosis   se
## Antivirus    -0.14 1.21
## Laptop       -0.32 1.11

hist(A5RQ2$Antivirus,
     main = "Histogram of Antivirus",
     xlab = "Value",
     ylab = "Frequency",
     col = "lightblue",
     border = "black",
     breaks = 20)

hist(A5RQ2$Laptop,
     main = "Histogram of Laptop",
     xlab = "Value",
     ylab = "Frequency",
     col = "lightgreen",
     border = "black",
     breaks = 20)

QUESTION

Q1) Check the SKEWNESS of the VARIABLE 1 histogram. In your opinion, does the histogram look symmetrical, positively skewed, or negatively skewed?

1. The histogram of Variable 1 looks mostly symmetrical with only a slight skew

Q2) Check the KURTOSIS of the VARIABLE 1 histogram. In your opinion, does the histogram look too flat, too tall, or does it have a proper bell curve?

1. The kurtosis of Variable 1 looks normal. it has a proper bell curve

Q3) Check the SKEWNESS of the VARIABLE 2 histogram. In your opinion, does the histogram look symmetrical, positively skewed, or negatively skewed?

1. The histogram of Variable 2 also looks mostly symmetrical with only slight skewness

Q4) Check the KUROTSIS of the VARIABLE 2 histogram. In your opinion, does the histogram look too flat, too tall, or does it have a proper bell curve?

1. The kurtosis of Variable 2 looks normal. it has a proper bell curve shape

shapiro.test(A5RQ2$Antivirus)

## 
##  Shapiro-Wilk normality test
## 
## data:  A5RQ2$Antivirus
## W = 0.99419, p-value = 0.8981

shapiro.test(A5RQ2$Laptop)

## 
##  Shapiro-Wilk normality test
## 
## data:  A5RQ2$Laptop
## W = 0.99362, p-value = 0.8559

QUESTION

Was the data normally distributed for Variable 1?

YES because p-value = 0.8981, which is GREATER than .05

Was the data normally distributed for Variable 2?

YES because p-value = 0.8559, which is GREATER than .05

library(ggplot2)

## 
## Attaching package: 'ggplot2'

## The following objects are masked from 'package:psych':
## 
##     %+%, alpha

library(ggpubr)

ggscatter(A5RQ2, x = "Antivirus", y = "Laptop",
          add = "reg.line",
          conf.int = TRUE,
          cor.coef = TRUE,
          cor.method = "pearson",
          xlab = "Variable Antivirus", ylab = "Variable Laptop")

QUESTION

Is the relationship positive (line pointing up), negative (line pointing down), or is there no relationship (line is flat)?

The relationship is positive since the line is pointing up

cor.test(A5RQ2$Antivirus, A5RQ2$Laptop, method = "pearson")

## 
##  Pearson's product-moment correlation
## 
## data:  A5RQ2$Antivirus and A5RQ2$Laptop
## t = 25.16, df = 120, p-value < 2.2e-16
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
##  0.8830253 0.9412249
## sample estimates:
##       cor 
## 0.9168679

Q1) What is the direction of the effect?

1. cor = 0.9168679. positive (+) correlation means as Variable V1 increases, Variable V2 increases

Q2) What is the size of the effect?

1. The relationship is strong because cor = 0.9168679 since ± 0.50 to 1.00 = strong

Summary

A Pearson correlation was conducted to examine the relationship between Antivirus liscenses purchased and number of Laptops purchased (n = 122). There was a statistically significant correlation between Antivirus (M = 50.18, SD = 13.36) and Laptop (M = 40.02, SD = 12.30). The correlation was positive and strong, r(120) = 0.9168679, p < .001.As Antivirus liscenses purchases increases, number of Laptops purchased increases.