====== Correlation ======
cor(data.frame, method=c("pearson", "kendall", "spearman"))
cor.test(data$acol, data$bcol, method=c("pearson", "kendall", "spearman"))
data("mtcars")
my_data <- mtcars[, c(1,2,3,4,5,6,7)]
head(my_data)
mpg cyl disp hp drat wt qsec
Mazda RX4 21.0 6 160 110 3.90 2.620 16.46
Mazda RX4 Wag 21.0 6 160 110 3.90 2.875 17.02
Datsun 710 22.8 4 108 93 3.85 2.320 18.61
Hornet 4 Drive 21.4 6 258 110 3.08 3.215 19.44
Hornet Sportabout 18.7 8 360 175 3.15 3.440 17.02
Valiant 18.1 6 225 105 2.76 3.460 20.22
>
install.packages("Hmisc")
library(Hmisc)
# rcorr(x, type = c("pearson","spearman"))
rcorr(as.matrix(my_data))
> rcorr(as.matrix(my_data))
mpg cyl disp hp drat wt qsec
mpg 1.00 -0.85 -0.85 -0.78 0.68 -0.87 0.42
cyl -0.85 1.00 0.90 0.83 -0.70 0.78 -0.59
disp -0.85 0.90 1.00 0.79 -0.71 0.89 -0.43
hp -0.78 0.83 0.79 1.00 -0.45 0.66 -0.71
drat 0.68 -0.70 -0.71 -0.45 1.00 -0.71 0.09
wt -0.87 0.78 0.89 0.66 -0.71 1.00 -0.17
qsec 0.42 -0.59 -0.43 -0.71 0.09 -0.17 1.00
n= 32
P
mpg cyl disp hp drat wt qsec
mpg 0.0000 0.0000 0.0000 0.0000 0.0000 0.0171
cyl 0.0000 0.0000 0.0000 0.0000 0.0000 0.0004
disp 0.0000 0.0000 0.0000 0.0000 0.0000 0.0131
hp 0.0000 0.0000 0.0000 0.0100 0.0000 0.0000
drat 0.0000 0.0000 0.0000 0.0100 0.0000 0.6196
wt 0.0000 0.0000 0.0000 0.0000 0.0000 0.3389
qsec 0.0171 0.0004 0.0131 0.0000 0.6196 0.3389
>