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a) Perform Time Series Decomposition on your project Y variable excluding the hold out period. Show me the smoothed Trend Values, Smoothed Cycle Values and Seasonal Indexes.
b) Show the seasonal indices and develop a one year time series plot of them. Do they indicate strong seasonality? How can you tell?
c) Evaluate the "Goodness To Fit" usingRMSE and MAPEerror measures .
d) Evaluate the residuals for the "Fit" period byindicating the residual distribution (random or not). Use a fit period residual time series plot, residuals ACFs and a histogram to determine if the Fit period residuals are random. If the residuals are not random state if you detect anytrend, cycle and seasonality.
e) Develop a one year monthly or weekly forecast or a two year quarterly forecast (for the hold out period) using the time series decomposition model you evaluated in c) above.
f) Evaluate the "Accuracy" of the forecast for the "hold out period" using the RMSE and MAPE measures used in partb) and comment them. Did the error measures increase, remain the same or decrease from the "Fit" to "Hold Out" or forecastperiod?
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