The closer that number is zero,

unfortunately the regression is not doing a very good job.

What do we see here?

R square is quite high.

It's about 89%.

That's a very high R square.

Typical R squares, 70 to 80%.

That's reasonably high.

What we can do from here, is now that we're convinced that the regression is

doing a good job of understanding how demand is weighting the price,

we can start using this regression to make predictions.

That's what we are after.

What we are after is how do we make demand predictions at different prices?

That's what we will do next.

So for doing that, we can take multiple steps.

We start out by looking at the regression line,

which is what we had shown earlier, and start inserting different prices.

We can first take the prices that are already in our data set and

compare how our predicted regression line, or

making predictions from the regression, is comparing with actual data.

That's what is shown first.

What we see here is actual data and

the predictive regression line are quite close to each other.

It's not surprising R square of the regression remember

which measures how good that regression is, is quite high.