Use a multiple regression model with dummy variables as follows to develop an equation to account for seasonal effects and trend in the data.

Let Q1 = 1 if Quarter 1, 0 otherwise; Q2 = 1 if Quarter 2, 0 otherwise; Q3 = 1 if Quarter 3, 0 otherwise;

Let Period = 1 refer to the observation in quarter 1 of year 1; Period = 2 refer to the observation in quarter 2 of year 1; ... and Period = 20 refer to the observation in quarter 4 of year 5.

Based on the seasonal effects in the data and linear trend, compute a forecast for the sales revenue in quarter 1 of year 6. (Carry at least two decimal values in the regression coefficients and round your final answer to two decimal values)

Year Quarter 1 1 1 1 2 2 2 2 3 3 3 3 N st Quarterly Sales Revenue ($1000s) 1 20 2 100 3 175 4 13 1 37 2 136 3 245 4 26 1 75 2 155 3 326 4 48 1 92 2 202 3 384 4 82 1 176 2 282 3 445 4 181 3 st 4 4 4 4 4 5 5 5 5 st Year Quarter 1 1 1 1 2 2 2 2 3 3 3 3 N st Quarterly Sales Revenue ($1000s) 1 20 2 100 3 175 4 13 1 37 2 136 3 245 4 26 1 75 2 155 3 326 4 48 1 92 2 202 3 384 4 82 1 176 2 282 3 445 4 181 3 st 4 4 4 4 4 5 5 5 5 st