I've seen this question on Chegg however this has a twist of the dummy variables being applied per quarter instead by month.

The vintage restaurant, on Captiva Island near Fort Myers, Florida, is owned and operated by Karen Payne. The restaurant just completed its third year of operation.During that time, Karen sought to establish a reputation for the restaurant as a high-quality dining establishment that specializes in fresh seafood. Through the efforts of Karen and her staff, her restaurant has become one of the best and fastest-growing restaurants on the island. To better plan for future growth of the restaurant, Karen needs to develop a system that will enable her to forecast food and beverage sales by month for up to one year in advance. Table 1 shows the value of food and beverage sales ($1000s) for the first three years of operation

Table 1- Food and Beverage Sales for the Vintage Restaurant ($1,000s)

Month	Year 1	Year 2	Year 3
January February March April May June July August September October November December	242 235 232 178 184 140 145 152 110 130 152 206	263 238 247 193 193 149 157 161 122 130 167 230	282 255 265 205 210 160 166 174 126 148 173 235

Perform an analysis of the sales data for the vintage restaurant. Prepare a report for Karen that summarizes your findings, forecasts, and recommendations, including the following:

• Construct a time series plot.
• Comment on the underlying pattern in the time series.
• Using the quarterly dummy variable approach, forecast sales for January through December of the fourth year. For instance, you would have three dummy variables quarter 1, quarter 2, and quarter 3 and quarter 4 is a baseline quarter. Quarter 1=1 if sales occurs in January, February, or March, otherwise, Quarter 1=0. Quarter 2=1 if sales occurs in April, May or June, otherwise, Quarter 2=0. Quarter 3=1 if sales occurs in July, August, or September, otherwise, Quarter 3=0.
• Assume that January sales for the fourth year turn out to be $295,000. What was your forecast error? If this error is large, Karen may be puzzled about the difference between your forecast and the actual sales value. What can you do to resolve her uncertainty in the forecasting procedure?