$\backslash$table$[[$Actual Sales January $-$ August$],[,],[,$Sales$],[$Month$,385],[$January$,389],[$February$,394],[$March$,398],[$April$,390],[$May$,410],[$June$,415],[$July$,410]]$

Based on this data, forecast sales for September using:

A four month moving average

A weighted three month moving average using these weights:

$\backslash$table$[[$August$,0\mathrm{.}6],[$July$,0\mathrm{.}3],[$June$,0\mathrm{.}1]]$

Exponential smoothing where $=0\mathrm{.}55($assume the forecast for August was $415)$

One of your employees developed two models for forecasting sales and tried to fit the model to past sales data, as shown below. You're not sure which method is better so you decide to calculate the Mean Absolute Percentage Error to explain which forecasting method $($Method $1$ or Method $2)$ is "better." Show your work in calculating the MAPE and make a conclusion as to which is a "better" method for predicting future sales.

Month Mo Counter Actual Sales Method $1$ Method $2$ e$1$ e$2|$e$1||$e$2||$e$1/$A $|$e$2|/$A

$\backslash$table$[[$J$,1,,,,,,,,[$e $\frac{1}{\frac{?}{?}}A,|e2|$