The sales data for two years are as follows. Data are aggregated with two months of sales in each “period.”

Months Sales Months Sales January–February March–April May–June July–August September–October November–December 109 104 150 170 120 100 January–February March–April May–June July–August September–October November–December 115 112 159 182 126 106

a. Plot the data.

b. Fit a simple linear regression model to the sales data.

c. In addition to the regression model, determine multiplicative seasonal index factors. A full cycle is assumed to be a full year.

d. Using the results from parts

(b) and (c), prepare a forecast for the next year.

TW-111