Question

Please help! ...................

Answer 1

Step By Step:

You can use the MAD formula to solve this problem.

`MAD = (\sum |forecast\ error|)/(n)`

This is saying sum all the forecast errors, which are the absolute deviations and then divide by the number of errors, which are the number of rows we have.

First sum up all the absolute deviations:

1 + 3 + 1 + 0 + 0 + 1 + 0 + 0 + 1 + 1 = 8

Second, count how many rows of data we have, which is 10, and divide 8 by 10

`MAD = (\sum |forecast\ error|)/(n)`

`MAD = (8)/(10) = (4)/(5) = .8`

.8 means that on average, each forecast missed the actual value by .8