forecasting

  

Over the past year, the demand for the White King flour based products have been inconsistent. The demand was beginning to have a seasonal pattern and the sales and production departments were concerned with the trend. They wanted to have an accurate forecast for the following year to enable them to develop short range and long range targets which they will use as their guide in establishing sales and production quotas. Demand for the White King flour based products last year were as follows: 
Month 
Demand
January
7200
February
5250
March 
6450
April
4500
May
5250
June 
4050
July
5250
August
3600
September
4800
October
3150
November
4050
December 
2550
Based on the data above:
1.  Using a simple four month moving average, find the forecast for January of the following year.
2.  Using a weighted moving average, (.40, .30, .20, .10) find the forecast for January of the following year.
3.  Using an exponential smoothing with ?=.2, find the forecast for January of the following year.
4.  Using simple linear regression analysis, calculate the regression equation for the preceding demand.
5.  Using simple linear regression with seasonality, compute the forecasts for the months of January, February, March, and April of the following year. 
6.What will be the forecast for the months of September, October, November and December