Applying Time Series Methodologies

Darlene Barrett

University of Phoenix

RES/342

Instructor: Leo M
September 11, 2011

Applying Time Series Methodologies

To forecast variables such as sales and demand, models such as simple linear regression, simple moving averages, and weighted moving averages. To be able to arrive at a reasonably accurate forecast, variation in the data provided needs to be analyzed. Variations can be cyclical, seasonal, secular, or irregular. This simulation illustrates the use of regression and time series methodologies to forecast the advertising budget, sales, and production levels in a company that manufactures denim products. Predicting, forecasting, and estimating can be a difficult task in business. In business, an incorrect sales forecast can have a snowballing effect and may lead to incorrect marketing, operating, and financial decisions. In this simulation, I will use these tools to make decisions at Blues Inc., a company that manufactures denim products. I am a Market Analyst who has been retained by Barbara Baderman, the CEO of Blues Inc to analyze the forecast at Blues Inc. The first week of my assignment and task is to predict the advertising budget. I selected sales as a variable for the regression analysis. The correlation of sales with the advertising budget is 0.96. This indicates that sales have a strong positive relationship with the advertising budget. Selecting sales was a good decision. Week