Consider the following time series data.

Quarter	Year 1	Year 2	Year 3
1	4	6	7
2	0	1	4
3	3	5	6
4	5	7	8

(a) Create the correct time series plot. Which 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. If required, round your answers to three decimal places. For subtractive or negative numbers, use a minus sign even if there is a + sign before the blank. (Example: -300) If the constant is 1, it must be entered in the box. Do not round intermediate calculations.

(c) Compute the quarterly forecasts for next year based on the model you developed in part (b). If required, round your answers to three decimal places. Do not round intermediate calculations.

(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 = for Quarter 1 in Year 1, t = 2 for Quarter 2 in Year 1,... t = 12 for Quarter 4 in Year 3. If required, round your answers to three decimal places. For subtractive or negative numbers, use a minus sign even if there is a + sign before the blank. (Example: -300)

(e) Compute the quarterly forecasts for next year based on the model you developed in part (d). Do not round your interim computations and round your final answer to three decimal places.

(f) Find MSE of the model developed in part (b) and the model developed in part (d). Which one is the more effective model? If required, round your intermediate calculations and final answer to three decimal places.

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If possible, for the tasks that require to use Excel, can you please help show me how to do those steps in Excel, especially how to create the time series plot in part a?

Thank you very much.