# Question

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 $308,000 in the first year of operation to $1,084,000 in the most recent year. The following data show the quarterly sales revenue in thousands of dollars:

a. Construct a time series plot. What type of pattern exists in the data?

b. Use a 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.

c. Based on the model you developed in part b, compute the quarterly forecasts for next

year.

d. Let t = 1 to refer to the observation in quarter 1 of year 1; t = 2 to refer to the observation in quarter 2 of year 1; . . . ; and t = 12 to refer to the observation in quarter 4 of year 3. Using the dummy variables defined in part b and t, develop an equation to account for seasonal effects and any linear trend in the time series.

e. Based upon the seasonal effects in the data and linear trend, compute the quarterly forecasts for next year.

f. Is the model you developed in part b or the model you developed in part d more effective?

Justify your answer.

a. Construct a time series plot. What type of pattern exists in the data?

b. Use a 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.

c. Based on the model you developed in part b, compute the quarterly forecasts for next

year.

d. Let t = 1 to refer to the observation in quarter 1 of year 1; t = 2 to refer to the observation in quarter 2 of year 1; . . . ; and t = 12 to refer to the observation in quarter 4 of year 3. Using the dummy variables defined in part b and t, develop an equation to account for seasonal effects and any linear trend in the time series.

e. Based upon the seasonal effects in the data and linear trend, compute the quarterly forecasts for next year.

f. Is the model you developed in part b or the model you developed in part d more effective?

Justify your answer.

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