So now, what I would like to show you is how to calculate the three forecast

accuracy measures that we discussed in the lecture in a spreadsheet.

So, we are going to start with the Mean Error.

In order to calculate the Mean Error, you need to calculate the error for

each period first, which then you can average together.

So, we get the error by taking

our demand minus our forecast and

there we have it in period three demands

24 forecast is 22 our error is 2.

Now as we copy this down, what we see is

we have positive and negative errors.

We over and underforecast and that's okay.

That's what we expect from the error.

To calculate the mean error, then what we

do is we go over here where I've created a spot for

it and we take the average of all of these

errors that we have, then we have it the mean

error in this example is -0.71.

Now, let's look at the absolute percent error.

So, the absolute percent error needs two parts.

One is we need to get an absolute error and

then we need to convert it into percent.

So, we get the absolute error by taking the absolute value.

We already calculated error, so I'll keep using that and

then we need to divide it by our demand to get it into a percent form.

So, the absolute value of the error that we

previously calculated divided by demand and

then all I need to do is copy this down over here.

And now,

I go in to this cell that I prepared here from our mean absolute percent error.

All I need to do is here.

Average all of these values together and here's our result.

On average, we have an error of 13.58%.

So every time we create a forecast, we're about almost 14% off.

We don't know in which direction on average, we're off.

But in general, this is how far we're off on average.

So now, we are looking at the squared error and

the squared error simply the squared error value.

We raise it to the second power.