Question
Which forecasting method or methods can you suggest? [Nave method, Moving Average, Single exponential smoothing, Holts method, Winters additive method, Winters multiplicative method, Additive Decomposition,
Which forecasting method or methods can you suggest? [Nave method, Moving Average, Single exponential smoothing, Holts method, Winters additive method, Winters multiplicative method, Additive Decomposition, Multiplicative Decomposition, Time Series Regression] a) Monthly sales (in thousands) of plastics ......................................................................................... b) Electricity Generation (billion kwh) ............................................................................................... c) Quarterly number of international visitors ...................................................................................... d) Daily Stock Price ($) .....
A)
b)
C)
d)
Monthly sales (in thousands) of plastics w 008 1995 1996 1997 1998 1999 2000 0.5 0.5 ACF PACF 0.0 0 0 -0.5 -0.5 T 15 T 15 5 10 20 10 20 Lag Lag -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0 500 1000 1500 2000 2500 3000 3500 4000 1950 5 1960 10 15 1970 PACF Electricity Generation (billion kwh) 0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0 1980 5 1990 10 2000 15 Quarterly number of international visitors w WA 2000 2002 2004 2006 2008 2010 0.8 0.8 0.6 0.6 0.4 0.4 0.2 0.2 PACF 0.0 0.0 -0.2 -0.2 -0.4 -0.4 1 15 10 15 5 10 Daily Stock Price ($) 0 20 40 60 80 0.3 0.3 0.2 0.2 0.1 L. -0.1 -0.2 -0.2 -0.3 -0.3 5 10 15 20 5 10 15 20 Monthly sales (in thousands) of plastics w 008 1995 1996 1997 1998 1999 2000 0.5 0.5 ACF PACF 0.0 0 0 -0.5 -0.5 T 15 T 15 5 10 20 10 20 Lag Lag -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0 500 1000 1500 2000 2500 3000 3500 4000 1950 5 1960 10 15 1970 PACF Electricity Generation (billion kwh) 0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0 1980 5 1990 10 2000 15 Quarterly number of international visitors w WA 2000 2002 2004 2006 2008 2010 0.8 0.8 0.6 0.6 0.4 0.4 0.2 0.2 PACF 0.0 0.0 -0.2 -0.2 -0.4 -0.4 1 15 10 15 5 10 Daily Stock Price ($) 0 20 40 60 80 0.3 0.3 0.2 0.2 0.1 L. -0.1 -0.2 -0.2 -0.3 -0.3 5 10 15 20 5 10 15 20
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