Develop an estimated regression equation


Assignment:

Review: 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.

Quarter

Year 1

Year 2

Year 3

1

1690

1800

1850

2

940

900

1100

3

2625

2900

2930

4

2500

2360

2615

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?

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Business Management: Develop an estimated regression equation
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