University of Phoenix Time Series Modeling Decomposition Worksheet

I’m working on a data analytics exercise and need an explanation to help me understand better.

Time series are particularly useful to track variables such as revenues, costs, and profits over time. Time series models help evaluate performance and make predictions.

• Time series decomposition seeks to separate the time series (Y) into 4 components: trend (T), cycle (C), seasonal (S), and irregular (I). What is the difference between these components?
• The model can be additive or multiplicative. When we do use an additive model? When do we use a multiplicative model?

The following table gives the gross federal debt (in millions of dollars) for the U.S. every 5 years from 1945 to 2000:

Construct a scatter plot with this data. Do you observe a trend? If so, what type of trend do you observe?

Use Excel to fit a linear trend and an exponential trend to the data. Display the models and their respective r^2.

Interpret both models. Which model seems to be more appropriate? Why?

Prepare your graphical and written response in a minimum of 500 words.