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Construct a scatter plot with data

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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 list 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?

Reference no: EM132845405

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