Goods and Services Test 2 Reading Notes

Movements over many years pop growth shifts culture

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movements over many years, pop growth, shifts, culture, income d.iii.2. Cyclical variations—business cycle, last more than a year d.iii.3. Seasonal variations—hotels on holidays d.iii.4. Random variations—unexpected events d.iv. Time series forecasting models d.iv.1. Simple moving average, weighted moving avg, exponential smoothing d.iv.2. Simple moving average d.iv.2.a. Avg more responsive if fewer data points used d.iv.2.b. Simple to use and easy to understand, doesn’t respond to trend changes quickly d.iv.3. Weighted moving average d.iv.3.a. Greater emphasis on more recent data to reflect changes in demand, not too good at trends d.iv.4. Exponential smoothing forecasting d.iv.4.a. With an alpha closer to 1, greater emphasis on recent data, more responsive to recent demand d.v. Trend-adjusted exponential smoothing forecasting model d.v.1. Two smoothing constants, one for smoothed forecast—alpha, and one for trend Beta d.vi. Linear trend forecasting model d.vi.1. Multiple regression d.vii. Associative forecasting models d.vii.1. Use regression analysis d.viii. Simple regression d.viii.1. Only one explanatory variable IV. Forecast accuracy
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a. Only 18% of companies forecast exceed 90% b. Forecast error, diff. between quantity demanded and forecast c. Mean absolute deviation (MAD) c.i.
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  • Fall '07
  • billthompson
  • Forecasting, Time series analysis, exponential smoothing forecasting, time series forecasting

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