The quarterly sales data (number of book sold) for Christian book over the past three years in California follow: (You can use Excel to compute the equation)

1. Construct a time series plot. What type of pattern exists in the data? This was not shown in the WebEx example I provided. But you can simply create this graph in Excel (Go to INSERT and look for charts under INSERT Tab). Basically you need to provide a 2-dimensional graph showing the trend of book sales over the given time period. The vertical line represents sale for Christian book, while the horizontal line represents quarter.

2. Use the following dummy variables to develop an estimated regression equation to account for any seasonal effects in the data: Quarter1=1 if the sales data point is in Quarter 1, otherwise Quarter 1=0; Quarter 2=1 if the sales data point is in Quarter 2, otherwise, Quarter 2=0; Quarter 3=1 if the sales data point is in Quarter 3, otherwise Quarter 3=0.

3. Compute the quarterly forecasts for next year.

4. 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 (2) and t, develop an estimated regression equation to account for seasonable effects and any linear trend in the time series. Based upon the seasonal effects in the data and linear trend, compute the quarterly forecasts for next year.

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