Year Quarter Demand 2014 1 68, 2 53, 3 57, 4 77, 2015 1 70, 2 61, 3 72, 4 96, 2016 1 80, 2 70, 3 87, 4 105
The above table shows the quarterly demand (in 100s units) of a product sold by a company during the past three years.
Use the regression analysis to fit an additive seasonal forecasting model with linear trend to the data set Model 1)
[1] Write clearly the estimated regression equation.
[2] What are the forecasts for each quarter in 2017?
[3] Construct a plot compare the predictions against the actual demand.
[4] Calculate MAD, MSE, and MAPE.
Use the regression analysis to fit a linear trend line to the data set (Model 2)
[4] Write clearly the estimated regression equation.
[5] What are the forecasts for each quarter in 2017?
[6] Construct a plot compare the predictions against the actual demand.
[7] Calculate MAD, MSE, and MAPE.
[8] Which model is a better forecasting model, Model 1 or Model 2? Briefly explain.