Question: Time series models help evaluate performance and make predictions. Consider the following and respond. Time series decomposition seeks to separate the time series (Y) into

Time series models help evaluate performance and make predictions. Consider the following and respond.

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

YearGross Federal Debt ($millions)

1945260,123

1950256,853

1955274,366

1960290,525

1965322,318

1970380,921

1975541,925

1980909,050

19851,817,521

19903,206,564

19954,921,005

20005,686,338

  • 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?

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