Determinant of the sample covariance - r

Question

new here!
I want to find the determinant of the pooled sample covariance of the given matrix. Can someone give a leading clue? (i have searched everywhere)
I have tried many things, this isn't the right solution (i have tried many) such as:
det(cov(dfdata))
mvec <- colMeans(dfdata) #sample mean vector#`enter code here`
covM <- cov(dfdata) #sample covariance matrix#
corM <- cor(dfdata) #sample correlation matrix#
covMnum <- cov(dfdatanum)
The following code is what i have developed:
##uploading the data
data2 <- read.table("file.tsv")
data3 <- read.table("file2.tsv")
data4 <- read.table("file3.tsv")
data5 <- read.table("file4.tsv")
## have a first look at data###
head(dfBull)
n <- nrow(dfBull) #n#
p <- ncol(dfBull) #p#
summary(dfBull)
##removing the first rove as it isnt neccesary
a <- data2[-(1), ]
b <- data3[-(1), ]
c <- data4[-(1), ]
d <- data5[-(1), ]
## finding the covariance
cv1 <- cov(as.numeric(a$V1), as.numeric(a$V2))
cv2 <- cov(as.numeric(b$V1), as.numeric(b$V2))
cv3 <- cov(as.numeric(c$V1), as.numeric(c$V2))
cv4 <- cov(as.numeric(c$V1), as.numeric(c$V2))
##This is the function im trying to use:
mat <- matrix(c(cv1,0,0,0,0,cv2,0,0,0,0,cv3,0,0,0,0,cv4), nrow=4, ncol=4, byrow=TRUE)
det(mat)`