Description

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:

Year

Gross Federal Debt ($millions)

1945

260,123

1950

256,853

1955

274,366

1960

290,525

1965

322,318

1970

380,921

1975

541,925

1980

909,050

1985

1,817,521

1990

3,206,564

1995

4,921,005

2000

5,686,338

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.