# Membuat dataset berdasarkan tabel yang diberikan
data <- data.frame(
Age = c(30.83, 58.67, 24.50, 27.83, 20.17),
Debt = c(0.000, 4.460, 0.500, 1.540, 5.625),
YearsEmployed = c(1.25, 3.04, 1.50, 3.75, 1.71),
Income = c(202, 560, 824, 3, 0) # Periksa nilai nol di sini
)
# Menampilkan data
knitr::kable(data)
| 30.83 |
0.000 |
1.25 |
202 |
| 58.67 |
4.460 |
3.04 |
560 |
| 24.50 |
0.500 |
1.50 |
824 |
| 27.83 |
1.540 |
3.75 |
3 |
| 20.17 |
5.625 |
1.71 |
0 |
# Menghitung matriks kovarians
cov_matrix <- cov(data)
# Menghitung eigenvalues dan eigenvectors
eig <- eigen(cov_matrix)
# Menampilkan hasil
cat("Eigenvalues:\n")
## Eigenvalues:
print(eig$values)
## [1] 1.321310e+05 2.031939e+02 4.936385e+00 7.643939e-01
cat("\n*Eigenvectors:*\n")
##
## *Eigenvectors:*
print(eig$vectors)
## [,1] [,2] [,3] [,4]
## [1,] -0.0149162116 0.99691360 0.063910703 -0.043083646
## [2,] 0.0017756745 0.06497029 -0.997623986 0.022849306
## [3,] 0.0007050725 0.04153604 0.025582743 0.998809183
## [4,] -0.9998869218 -0.01472719 -0.002707029 0.001387607
# Menampilkan Variance-Covariance Matrix
cat("Variance-Covariance Matrix:\n")
## Variance-Covariance Matrix:
print(cov_matrix)
## Age Debt YearsEmployed Income
## Age 231.361400 9.345663 6.999375 1967.6875
## Debt 9.345663 6.187675 0.605225 -234.7763
## YearsEmployed 6.999375 0.605225 1.182050 -93.2750
## Income 1967.687500 -234.776250 -93.275000 132101.2000
# Menghitung Correlation Matrix dengan validasi nilai nol
if (all(data$Income == 0)) {
cat("Peringatan: Semua nilai dalam kolom Income adalah nol, matriks korelasi tidak dapat dihitung dengan benar.\n")
} else {
cor_matrix <- cor(data)
cat("Correlation Matrix:\n")
print(cor_matrix)
}
## Correlation Matrix:
## Age Debt YearsEmployed Income
## Age 1.0000000 0.2470022 0.4232489 0.3559240
## Debt 0.2470022 1.0000000 0.2237872 -0.2596791
## YearsEmployed 0.4232489 0.2237872 1.0000000 -0.2360445
## Income 0.3559240 -0.2596791 -0.2360445 1.0000000