Research Paper on:
Time Series Methodologies

Unformatted Sample Text from the Research Paper:
planners in the sense that time series data from the market in which a business operates suggests potential directions for that business budgeting, sales, and production concerns. As an analyst  for Blues, Inc., I have been charged with submitting a memo to Myra Reid, the Vice President of Production, with my forecasts for the next year. When allocating budget to  different aspects of the business such as advertising or production, it is important to anticipate the performance of the business within the market to assure that sufficient resources are directed  to each aspect in the correct proportion. Making use of linear regression techniques, I looked at our advertising budget in light of its relationship to a variety of factors and  ascertained that the factor with the highest correlation to our advertising budget is sales. Assuming a 6% share of a market predicted to be 40 billion this year, an advertising  budget of 162 million will be in keeping with past trends and provide room for growth. As far as production goes, I made an assessment by subjecting time series data  to a weighted moving average and came to the conclusion that our organization can anticipate sales of roughly 46 million units during the coming year. This was determined by subjecting  the data to a number of models and assessing which presented the lowest mean square error. However, because of policy that requires us to keep 10% safety stock on hand,  determining sales is not sufficient to determine needed production levels. It is vital to break production predictions down into quarterly assessments. Repressing seasonal  outliers and subjecting the data to a centered moving average of the last 6 years worth of data, I have determined that our total sales can best be projected at