Review chapter 6.5: Seasonality (pp. 223-229) and answer the following questions.
The quarterly sales data (number of book sold) for Christian book over the past three years in California follow: You must use Excel to compute the time series (regression) equation
1. Construct a time series plot. What type of pattern exists in the data?
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 (b) 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.
5. This is an open-ended essay question. Based on the result in 4, what factors might lead to the highest Christian book sales in quarter 3? You may quote bible verses in 2 Corinthians 9:10 or Colossians 1:10.
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