$\backslash$table$[[4,26],[5,18],[6,17],[7,21],[8,19],[9,22],[10,18],[11,17],[12,21]]$

Show the exponential smoothing forecasts using $a=0\mathrm{.}1,$ and $a=0\mathrm{.}2.$

$\backslash$table$[[,\backslash$table$[[$Exponential$],[$Smoothing$]]],[$Week $a=0\mathrm{.}1,0,a,,],[13,,]]$

Applying the MSE measure of forecast accuracy, would you prefer a smoothing constant of $a=0\mathrm{.}1$ or $a=0\mathrm{.}2$ for the gasolir

An $$ smoothing constant provides the more accurate forecast, with an overall MSE of Are the results the same if you apply MAE as the measure of accuracy?

An $$ smoothing constant provides the more accurate forecast, with an overall MAE of What are the results if MAPE is used?

An $$ smoothing constant provides the more accurate forecast, with an overall MAPE of