Time series analysis allows researchers to predict future values of time series variables. In time series analysis, researchers look for systematic patterns in the data in order to make inferences about future data outcomes.

The purpose of this online paper is to predict future sales of Wilmore Paper Company as they relate specifically to the advertising budget allocated. This quarterly data for Wilmore Paper Company was collected on this relationship for nine years from 2000 to 2008.

In order to find the model that best predicts futuer sales, the data was analyzed using nine different models: Linear Function, Logistic Function, Bower Bound Function, Modified Exponential Function, Power Function, Logarithmic Function, Square-Root Function, and Quadratic Function. After analyzing the date, the best budgeting model was chosen. The following five steps: (1) Specification, (2) Estimation, (3) Verification, and (4) Validation are used to explain the selected budgeting model.

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