d. Examine the additive model. Which month has the highest average sales during the year. What does the estimated trend coefficient in the model A mean? e. Examine the multiplicative model. What does the coefficient of October mean? What does the estimated trend coefficient in the model B mean? f. Use the best model type from part (c) to forecast the sales in January 2002. Think carefully which data to use for model fitting in this case. g. Plot the ACF and PACF plot until lag 20 of the residuals obtained from training set of the best model chosen. Comment on these plots and think what AR(p) model could be a good choice? h. Fit an AR(p) model as you think appropriate from part (h) to the training set residuals and produce the regression coefficients. Was your intuition at part (h) correct? i. Now, using the best regression model and AR(p) model, forecast the sales in January 2002. Think carefully which data to use for model fitting in this case