Consider the following time series data. Quarter Year 1 Year 2 Year 3 1 10 12 13 2 8 9 12 3 9 1 1 12 4 1 1 13 14 (a) Construct a time series plot. 15 15 15 14 14 14 E 13 E 13 E 13 g 12 g 12 g 12 E 11 E 11 E 11 g 10 g 10 g 10 u 9 u 9 u 9 .5 s g s g s 7 7 7 6 6 6 123412341234 123412341234 123412341234 Year 1 Year 2 Year 3 Year 1 Year 2 Year 3 Year 1 Year 2 Year 3 O Year/Quarter (D O Year/Quarter G) O Year/Quarter 15 14 E 13 g 12 E 11 E 10 I" 9 E s 7 6 1 2 3 4 1 2 3 4 1 2 3 4 Year 1 Year 2 Year 3 Year/Quarter (D What type of pattern exists in the data? O The time series plot shows a horizontal pattern and no seasonal pattern in the data. 0 The time series plot shows a linear trend and no seasonal pattern in the data. @ The time series plot shows a linear trend and a seasonal pattern in the data. 0 The time series plot shows a horizontal pattern, but there is also a seasonal pattern in the data. if (h) Use the following dummy variables to develop an estimated regression equation to aocount for any seasonal and linear trend effects in the data. (Round your numerical values to two decimal places.) x1 = 1 if quarter 1, 0 otherwise; x2 = 1 if quarter 2, 0 otherwise; x3 = 1 if quarter 3, 0 otherwise ~ u X (c) Compute the quarterly forecasts for next year. (Round your answers to one decimal place.) quarter 1 forecast E: X quarter 2 forecast E: x quarter 3 forecast E: X quarter 4 forecast E: x