Reference no: EM132845405
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?