1. Use a multiple regression model with dummy variables as follows to develop an equation to account for seasonal effects in the data. Qtr1 = 1 if Quarter 1, 0 otherwise; Qtr2 = 1 if Quarter 2, 0 otherwise; Qtr3 = 1 if Quarter 3, 0 otherwise. If required, round your answers to three decimal places. For subtractive or negative numbers use a minus sign even if there is a + sign before the blank. (Example: -300) Value___ =____ + _____ Qtr1 + _____ Qtr2 + ______ Qtr3 + ______ t
2. Compute the quarterly forecasts for next year. If required, round your answers to two decimal places. Quarter 1 forecast = Quarter 2 forecast = Quarter 3 forecast = Quarter 4 forecast =

eBook Problem 6-01 (Algorithmic) Consider the fallowing time series data. Week Value 1 20 2 14 3 15 4 11 5 6 17 15 Using the naive method (most recent value) as the forecast for the next week, compute the following measures of forecast accuracy a. Mean absolute error. If required, round your answer to one decimal place. 5 x b. Mean squared error. If required, round your answer to one decimal place. 29 x c. Mean absolute percentage error. If required, round your intermediate calculations and final answer to two decimal places. 32.55 X 4 d. What is the forecast for work ?? If required, mund your answer to twa recimal plare. 15 Feedback Chwe My Wurs Parlialy correct