local varnum=wordcount("$col_vars $row_vars")												//count how many variables are in total
	di "`varnum'"
	
	* change variable names, this is made to use a code found in internet to compute p-values of correlations

	local c = 1
	foreach k in $row_vars $col_vars {
		rename `k' var`c'
		local c = `c'+1
	}

			* CREATE THE FOUR MATRICES THAT WILL CONTAIN THE RESULTS

			matrix C = I(`varnum')																				//Coef. matrix
			matrix N = I(`varnum')
			matrix T= I(`varnum')
			matrix P= I(`varnum')																				//P-value matrix

			forvalues i=1(1)`varnum' {
				forvalues j=1(1)`i'{ 
				corr var`i' var`j'
			* GET THE CORRELATION AND RESULTS, IF THERE HAS NOT BEEN ERROR 
				if _rc==0{
			* RHO IS THE CORRELATION
				matrix C[`i',`j']=r(rho)
				matrix C[`j',`i']=r(rho)
			* N IS THE NUBMER OF OBSERVATIONS
				matrix N[`i',`j']=r(N)
				matrix N[`j',`i']=r(N)
			* P IS THE P-VALUES
				matrix P[`i',`j']=2*ttail(r(N)-2,/*
					*/ abs(r(rho))*sqrt(r(N)-2)/sqrt(1-r(rho)^2))
				matrix P[`j',`i']=P[`i',`j']
			* T IS THE T-STATISTICS
				matrix T[`i',`j']= abs(r(rho))*sqrt(r(N)-2)/sqrt(1-r(rho)^2)
				matrix T[`j',`i']=T[`i',`j']
				}
				else{
			* IF 	-COR- HAD AN ERROR, PUT RESULTS TO MISSING
				matrix C[`i',`j']=.
				matrix C[`j',`i']=.
				matrix N[`i',`j']=.
				matrix N[`j',`i']=.
				matrix P[`i',`j']=.
				matrix P[`j',`i']=.
				matrix T[`i',`j']=.
				matrix T[`j',`i']=.
				}
			* PUT APPROPRIATE VALUES ON THE DIAGONAL
				matrix C[`i',`i']=1
				matrix N[`i',`i']=r(N)
				matrix P[`i',`i']=.
				matrix T[`i',`i']=.
				}
			}


			*PRINT RESULTS
			display as text "sample correlations" 
			matrix list C, format(%6.4f) noheader
			
			display as text "number of observations"
			matrix list N,   noheader

			display as text "t-statistics"
			matrix list T,   noheader


			display as text "p-values"
			matrix list P,   noheader


	local c = 1
	foreach k in $row_vars $col_vars {
		rename var`c' `k' 
		local c = `c'+1
	}