```
#' Testing to see which participant to delete to get significance.
#' A way to look for outlayers.
#' The correlation is between two variables
#'
#' @param DFDEL Data frame with two variables.
#' The dataframe should have an Index and two variables
#' @return cortestResults - Data frame with the correlation and significance.
#' between the two varibels and without one participant each time.
#' @note Use wisely. You need the package library(Hmisc)
#' @examples
#' FindDelRow(DF)
CorrDelRow <- function(DFDEL)
{
# Building main vars and Final DF
delline <- 1
row <- 1
counter <- 1
DF <- DFDEL %>% setNames(c("ID", "Var1", "Var2"))
cortestResults <- data.frame(R = as.numeric(),
P = as.numeric(),
n = as.numeric(),
no = as.numeric())
# Looping
for (counter in 1:NROW(DF)) {
DForginal <- DF
DFTemp <- DF[-delline,]
cortest <- rcorr(as.matrix(DFTemp))
cortestResults[row,1] <- cortest$r[3,2]
cortestResults[row,2] <- cortest$P[3,2]
cortestResults[row,3] <- cortest$n[3,2]
cortestResults[row,4] <- DF$ID[delline]
counter <- counter + 1
delline <- delline + 1
row <- row + 1
} #End Loop
return(cortestResults)
} #End Function
```

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.