Korelasi Pearson

#korelasi pearson

# Masukkan data
data <- data.frame(
  y = c(57.5, 52.8, 61.3, 67, 53.5, 62.7, 56.2, 68.5, 69.2),
  x1 = c(78, 69, 77, 88, 67, 80, 74, 94, 102),
  x2 = c(2.75, 2.15, 4.41, 5.52, 3.21, 4.32, 2.31, 4.30, 3.71),
  x3 = c(29.5, 26.3, 32.2, 36.5, 27.2, 27.7, 28.3, 30.3, 28.7)
)

# Matriks korelasi
R <- cor(data)

heatmap(R, Rowv=NA, Colv=NA)

library(pheatmap)

pheatmap(R, display_numbers=TRUE)

pheatmap(R, 
         display_numbers=TRUE,
         cluster_rows=FALSE,
         cluster_cols=FALSE)

pheatmap(R)

y <- c(57.5, 52.8, 61.3, 67, 53.5, 62.7, 56.2, 68.5, 69.2)

x1 <- c(78, 69, 77, 88, 67, 80, 74, 94, 102)

x2 <- c(2.75, 2.15, 4.41, 5.52, 3.21, 4.32, 2.31, 4.30, 3.71)

x3 <- c(29.5, 26.3, 32.2, 36.5, 27.2, 27.7, 28.3, 30.3, 28.7)

data <- cbind(y, x1, x2, x3)
data

##          y  x1   x2   x3
##  [1,] 57.5  78 2.75 29.5
##  [2,] 52.8  69 2.15 26.3
##  [3,] 61.3  77 4.41 32.2
##  [4,] 67.0  88 5.52 36.5
##  [5,] 53.5  67 3.21 27.2
##  [6,] 62.7  80 4.32 27.7
##  [7,] 56.2  74 2.31 28.3
##  [8,] 68.5  94 4.30 30.3
##  [9,] 69.2 102 3.71 28.7

R <- cor(data, method = "pearson")
R

##            y        x1        x2        x3
## y  1.0000000 0.9470919 0.7611425 0.5603295
## x1 0.9470919 1.0000000 0.5340188 0.3899864
## x2 0.7611425 0.5340188 1.0000000 0.7844691
## x3 0.5603295 0.3899864 0.7844691 1.0000000

heatmap(R)

install.packages("pheatmap")

## Warning: package 'pheatmap' is in use and will not be installed

library(pheatmap)

pheatmap(R, 
         display_numbers = TRUE,
         cluster_rows = FALSE,
         cluster_cols = FALSE)