Answer Happy

South Shore Construction builds permanent docks and seawalls along the southern shore of Long Island, New York. Although the firm has been in business only five years, revenue has increased from $307,000 in the first operation to $1,090,000 in the most recent year. The following data show the quarterly sales revenue in thousands of dollars. Quarter Year 4 Year 5 Year 1 15 Year 2 29 Year 3 76 1 89 162 102 127 147 203 287 3 168 240 328 376 453 4 22 25 43 88 188 a. Construct a time series plot. 1. Time Series Value 450 400 350 1300 250 200 150 100 50 8 9 10 11 12 13 14 15 16 17 18 19 20 Time Period (t) L-50 1 2 3 4 5 I 6 7 2
2. Time Series Value 450 400 350 300 250 tum M 200 150 100 50 ++++ 2 3 4 5 9 10 11 12 13 14 15 16 17 18 19 20 1 L-50 Time Period (t) Time Series Value 450 400 350 300 250 200 150 100 50 **|****|****|****|**** 1 L-50 9 10 11 12 13 14 15 16 17 18 19 20 Time Period (t) 3. 2 -M 3 4 5 6 () 6 - 00 7 8 - 00 7 8
4. Time Series Value 450 400 350 300 250 200 150 100 50 2 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 Time Period (t) -50 Time series plot 2 What type of pattern exists in the data? There appears to be a seasonal pattern in the data and perhaps a upward linear trend b. Use the following dummy variables to develop an estimated regression equation to account for any 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. Round your answers (in thousands of dollars) to whole number. Revenue = 6.667 + 8 Qtrl + Qtr2 + Qtr3 Based only on the seasonal effects in the data, compute estimates of quarterly sales for year 6. Round your answers to whole number. Quarter 1 forecast $ Quarter 2 forecast $ X thousands * thousands X Quarter 3 forecast $ thousands Quarter 4 forecast $ thousands c. Let Period = 1 to refer to the observation in quarter 1 of year 1; Period = 2 to refer to the observation in quarter 2 of year 1; ... and Period 20 to refer to the observation in quarter 4 of year 3. Using the dummy variables defined in part (b) and Period, develop an estimated regression equation to account for seasonal effects and any linear trend in the time series. Round your answers (in thousands of dollars) to whole number. Enter negative value as negative number. 3
There appears to be a seasonal pattern in the data and perhaps a upward linear trend b. Use the following dummy variables to develop an estimated regression equation to account for any 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. Round your answers (in thousands of dollars) to whole number. Revenue = 6.667 8 Qtrl + X Qtr2 + Qtr3 Based only on the seasonal effects in the data, compute estimates of quarterly sales for year 6. Round your answers to whole number. Quarter 1 forecast $ thousands Quarter 2 forecast $ thousands Quarter 3 forecast $ thousands Quarter 4 forecast $ thousands c. Let Period = 1 to refer to the observation in quarter 1 of year 1; Period=2 to refer to the observation in quarter 2 of year 1;... and Period 20 to refer to the observation in quarter 4 of year 3. Using the dummy variables defined in part (b) and Period, develop an estimated regression equation to account for seasonal effects and any linear trend in the time series. Round your answers (in thousands of dollars) to whole number. Enter negative value as negative number. The regression equation is: Revenue = Qtrl + Qtr2 + Qtr3+ Period Based upon the seasonal effects in the data and linear trend, compute estimates of quarterly sales for year 6. Round your answers to whole number. Quarter 1 forecast $ thousands thousands Quarter 2 forecast $ Quarter 3 forecast $ * thousands Quarter 4 forecast $ thousands