# Question

Consider the following time series data:

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

b. Use a multiple 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. Compute the quarterly forecasts for next year based on the model you developed in part b.

d. Use a multiple regression model to develop an equation to account for trend and seasonal effects in the data. Use the dummy variables you developed in part b to capture seasonal effects and create a variable t such that t = 1 for quarter 1 in year 1, t = 2 for quarter 2 in year 1, . . . t = 12 for quarter 4 in year 3.

e. Compute the quarterly forecasts for next year based on the model you developed in part d.

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 multiple 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. Compute the quarterly forecasts for next year based on the model you developed in part b.

d. Use a multiple regression model to develop an equation to account for trend and seasonal effects in the data. Use the dummy variables you developed in part b to capture seasonal effects and create a variable t such that t = 1 for quarter 1 in year 1, t = 2 for quarter 2 in year 1, . . . t = 12 for quarter 4 in year 3.

e. Compute the quarterly forecasts for next year based on the model you developed in part d.

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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