Below are gasoline prices downloaded from https:$//$www$.$eia.gov$/$petroleum$/$gasdiesel$/$

a Create a $3-$week simple moving average forecast of the price.

Compute the mean absolute deviation,$$the mean absolute percentage error,$$and the sum of squared errors for this forecast.

b Create an expontential smoothing forecast of the price using $0\mathrm{.}9$ as a smoothing constant.

Compute the mean absolute deviation,$$the mean absolute percentage error,$$and the sum of squared errors for this forecast.

c Compare the two forecasts. Which of the two forecasting methods gives smaller errors?

Forecast one week ahead $($first week of January $2023)$ using each of these $2$ methods. Do you get similar results?

d Create a plot with your data and your forecasts.

Which of the two forecasting methods appear to perform better based on your graphs?