The purchasing agent for a hospital has collected data over the last five years on average monthly unit prices for a commonly used surgical item.

She believes that an accurate forecast of price would help improve the timing of her buying. Using the oldest four years of data as the base data and saving the most recent data (last year) for checking the forecast accuracy, do the following:
a. Plot the data on a graph. What important observations can you make about the data that would be useful to forecasting?
b. Construct a classic time series decomposition forecasting model based on two full years of data (years 2 and 3) and compute the error of the forecast (SF) for the last full year.
c. Construct an exponential smoothing model (α = 0.14, β = 0.01, and γ = 0.7) with level, trend, and seasonal components, and compute SF for the last year.
d. Create a weighted average model that combines both model types.

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