By the way a useful function would be some sort of "code-optimizer", automatically giving a suggestion for faster code!

sec;
for(ii=1;ii<1000;ii++)
{
	dt=col(1)[ii]-col(1)[ii-1];
	col(3)=col(2)[ii]*dt;
}
sec -e elapsed;
type Bjorn's Script takes $(elapsed) seconds;
type;
sec;
for(ii=1;ii<1000;ii++)
{
	dt=col(1)[ii]-col(1)[ii-1];
	col(3)[ii]=col(2)[ii]*dt;
}
sec -e elapsed;
type Bjorn's corrected script takes $(elapsed) seconds;
type;
sec;
copy -b 1 col(1) col(3) -b 2 -e 999;
col(3)*=-1;
col(3)+=col(1);
col(3)*=col(2);
sec -e elapsed;
type Mike's script takes $(elapsed) seconds;
type;

Bjorn's Script takes 2.319 seconds
Bjorn's corrected script takes 1.723 seconds
Mike's script takes 0.006 seconds

I should point out that Origin has a built-in function that finds the differences between rows of data, but since it offsets the results by one row it would yield a different result and since it internally creates a temporary dataset it doesn't have as much speed advantage as Mike's use of operator assignment notation which works 'in-place' on the data without the overhead of new memory allocation. Here is an example of the DIFF() function in use:

sec;
col(3)=diff(col(1));
col(3)*=col(2);
sec -e elapsed;
type My script takes $(elapsed) seconds;
type;

My script takes 0.006 seconds

Again, I am not calculating the same values as Bjorn or Mike, and I only mean to illustrate the DIFF() function.

for(ii=1;ii<1000;ii++)
{
col(3)[ii]=col(1)[ii]-col(1)[ii-1];
};
col(3)*=col(2);

Then eliminate the for-loop entirely by using the copy command:

copy -b 1 col(1) col(3) -b 2 -e 999;
// col(3) will be a copy of col(1) with the cells offset by one row
// and the subtractions can now be performed using vector notation
col(3)*=-1; col(3)+=col(1);
col(3)*=col(2);

for (n=1;n<20;n++) {
   data1_a[n]=n; data1_b[n]=data1_a[n]; 
}

for (n=20;n<40;n++) {
   data1_a[n]=n; data1_b[n]=data1_a[n]^2; 
}