Data

library(csv)
library(readr)

data1 <- suppressMessages(read_csv2("D:/DHEA/tips_simulated_500.csv"))
total_bill <- data1$total_bill
pajak      <- data1$pajak
head(data1)
## # A tibble: 6 × 2
##   total_bill pajak
##        <dbl> <dbl>
## 1       22.0  3.7 
## 2       16.9  3.18
## 3       23.2  2.83
## 4       30.2  4.87
## 5       16.1  2.21
## 6       16.1  2.26

Statistik deskriptif sederhana

summary(data1)
##    total_bill        pajak      
##  Min.   : 5.00   Min.   :1.000  
##  1st Qu.:12.39   1st Qu.:1.900  
##  Median :18.10   Median :2.655  
##  Mean   :18.17   Mean   :2.741  
##  3rd Qu.:23.09   3rd Qu.:3.470  
##  Max.   :48.82   Max.   :8.980

Standar deviasi

sd(total_bill)
## [1] 7.602391
sd(pajak)
## [1] 1.168081

Uji korelasi Pearson

hasil_korelasi <- cor.test(total_bill, pajak, method = "pearson") 
# Menampilkan hasil 
print(hasil_korelasi)
## 
##  Pearson's product-moment correlation
## 
## data:  total_bill and pajak
## t = 63.645, df = 498, p-value < 2.2e-16
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
##  0.9332055 0.9525391
## sample estimates:
##       cor 
## 0.9436722

koefisien korelasi dan p-value

r <- hasil_korelasi$estimate
p_val <- hasil_korelasi$p.value
print(hasil_korelasi)
## 
##  Pearson's product-moment correlation
## 
## data:  total_bill and pajak
## t = 63.645, df = 498, p-value < 2.2e-16
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
##  0.9332055 0.9525391
## sample estimates:
##       cor 
## 0.9436722
cat("\nKoefisien Korelasi Pearson:", r, "\n")
## 
## Koefisien Korelasi Pearson: 0.9436722
cat("P-value:", p_val, "\n")
## P-value: 2.372525e-241

Keputusan uji dengan alpha 0.05

alpha <- 0.05
if(p_val < alpha){
  cat("Keputusan: Tolak H0: Terdapat korelasi yang signifikan antara total_bill dan pajak pada alpha =", alpha, "\n")
} else {
  cat("Keputusan: Gagal tolak H0: Tidak terdapat korelasi yang signifikan antara total_bill dan pajak pada alpha =", alpha, "\n")
}
## Keputusan: Tolak H0: Terdapat korelasi yang signifikan antara total_bill dan pajak pada alpha = 0.05

Scatterplot

plot(total_bill, pajak, 
main = "Scatter Plot total bill vs pajak", 
xlab = "total bill", 
ylab = "pajak", 
pch = 19, col="blue") 
abline(lm(pajak ~ total_bill), col = "red", lwd = 2)