PrakMetstat_Pert2

library(stats)
library(car)

## Warning: package 'car' was built under R version 4.5.3

## Loading required package: carData

## Warning: package 'carData' was built under R version 4.5.3

library(lmtest)

## Warning: package 'lmtest' was built under R version 4.5.3

## Loading required package: zoo

## Warning: package 'zoo' was built under R version 4.5.3

## 
## Attaching package: 'zoo'

## The following objects are masked from 'package:base':
## 
##     as.Date, as.Date.numeric

library(zoo)

data <- read.table(file.choose(), header = TRUE)
data

##           Kabupaten   IPM   IPG
## 1           Pacitan 87.59 72.26
## 2          Ponorogo 95.41 74.65
## 3        Trenggalek 93.64 73.39
## 4       Tulungagung 95.84 75.88
## 5            Blitar 94.35 74.43
## 6            Kediri 94.14 76.09
## 7            Malang 89.82 74.45
## 8          Lumajang 90.30 71.02
## 9            Jember 86.80 71.57
## 10       Banyuwangi 88.31 75.17
## 11        Bondowoso 91.57 71.72
## 12        Situbondo 88.21 71.87
## 13      Probolinggo 87.17 71.65
## 14         Pasuruan 92.06 73.02
## 15         Sidoarjo 95.46 83.35
## 16        Mojokerto 92.85 77.46
## 17          Jombang 91.62 76.37
## 18          Nganjuk 95.08 75.89
## 19           Madiun 93.62 75.47
## 20          Magetan 95.01 77.58
## 21            Ngawi 94.36 74.43
## 22       Bojonegoro 92.56 73.74
## 23            Tuban 89.71 73.15
## 24         Lamongan 90.86 76.81
## 25           Gresik 92.01 79.69
## 26        Bangkalan 88.42 68.15
## 27          Sampang 87.39 67.23
## 28        Pamekasan 88.04 71.64
## 29          Sumenep 83.57 70.54
## 30      Kota_Kediri 96.36 82.71
## 31      Kota_Blitar 98.11 82.03
## 32      Kota_Malang 97.04 85.55
## 33 Kota_Probolinggo 97.52 78.50
## 34    Kota_Pasuruan 98.59 79.52
## 35   Kota_Mojokerto 95.65 82.35
## 36      Kota_Madiun 96.05 85.12
## 37    Kota_Surabaya 95.96 85.65
## 38        Kota_Batu 91.87 80.35

summary(data)

##   Kabupaten              IPM             IPG       
##  Length:38          Min.   :83.57   Min.   :67.23  
##  Class :character   1st Qu.:89.74   1st Qu.:72.45  
##  Mode  :character   Median :92.70   Median :75.32  
##                     Mean   :92.45   Mean   :76.06  
##                     3rd Qu.:95.45   3rd Qu.:79.27  
##                     Max.   :98.59   Max.   :85.65

boxplot(data$IPG, data$IPM, names = c("IPG", "IPM"), main = "Boxplot IPG dan IPM", col = "pink")

plot (data$IPM, data$IPG, xlab = "Indeks Pembangunan Manusia (IPM)", ylab = "Indeks Pembangunan Gender", main = "Scatter Plot IPM dan IPG", pch = 19)

abline(lm(IPG ~ IPM, data = data), col = "blue", lwd = 2)

shapiro.test(data$IPM)

## 
##  Shapiro-Wilk normality test
## 
## data:  data$IPM
## W = 0.96435, p-value = 0.2621

shapiro.test(data$IPG)

## 
##  Shapiro-Wilk normality test
## 
## data:  data$IPG
## W = 0.9572, p-value = 0.1537

cor.test(data$IPM, data$IPG, method = "pearson")

## 
##  Pearson's product-moment correlation
## 
## data:  data$IPM and data$IPG
## t = 6.8672, df = 36, p-value = 4.906e-08
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
##  0.5707799 0.8645958
## sample estimates:
##       cor 
## 0.7530543