1) Assume the following time series data representing the number of sales per day your company’s employees make. Year-Quarter | t | Yt | 2001-1 | 1 | 17 | 2001-2 | 2 | 26 | 2001-3 | 3 | 21 | 2001-4 | 4 | 15 | 2002-1 | 5 | 19 | 2002-2 | 6 | 18 | 2002-3 | 7 | 21 | 2002-4 | 8 | 23 | a) Use Applet #16 to calculate the seasonal index numbers for the four quarters. b) Interpret what each of the four indices you computed in (a) mean in terms of how your company’s sales fluctuate in each quarter. 2) a) Given the following data and seasonal indices S1 = 0.8, S2 = 1.4, S3 = 0.7, S4 = 1.3, deseasonalize the following data. (Be careful!). Show your work. Year | Quarter | t | Yt | dt | 2001 | 3 | 1 | 480 | | 2001 | 4 | 2 | 810 | | 2002 | 1 | 3 | 510 | | 2002 | 2 | 4 | 860 | | 2002 | 3 | 5 | 440 | | b) Why would you want to deseasonalize data? Can you think of an example when deseasonalized data would be necessary for analysis?
3) A simple regression model was run on the following time series, representing the number of company employees per quarter, to establish the linear trend. Use this information to answer questions (a), (b) and (c) below. Year | Quarter | t | Yt | St | dt | 2001 | 3 | 1 | 1050 | 0.9 | 1166.67 | 2001 | 4 | 2 | 1200 | 1.1 | 1090.91 | 2002 | 1 | 3 | 980 | 0.85 | 1152.94 | 2002 | 2 | 4 | 1140 | 1.05 | 1085.71 | 2002 | 3 | 5 | 1020 | 0.9 | 1133.33 | (a) Which column should be used as the independent (X) variable and which should be used as the dependent (Y) variable in the regression model? (b) Given the Excel regression output below, write the trend line for the above time series. (c) Use the regression line from part (b) to compute the value of the trend component for t = 4. (Show how you arrived at your answer.) (d) Interpret the slope of the trend line. That is, how much, on