Assignment:
Referring to Problem below, the managers of DataNet, the Internet company through which users can purchase products like airline tickets, need to forecast monthly call volumes in order to have sufficient capacity. Develop a single exponential smoothing model using α = 0.30. Use as a starting value the average of the first six months’ data.
a. Compute the MAD for this model.
b. Plot the forecast values against the actual data.
c. Use the same starting value but try different smoothing constants (say, 0.10, 0.20, 0.40, and 0.50) in an effort to reduce the MAD value.
d. Reflect on the type of time series for which the single exponential smoothing model is designed to provide forecasts. Does it surprise you that the MAD for this method is relatively large for these data? Explain your reasoning.
Problem: Data Net is an Internet service through which clients can find information and purchase various items such as airline tickets, stereo equipment, and listed stocks. Data Net has been in operation for four years. Data on monthly calls for service for the time that the company has been in business are in the data file called Data Net.
a. Plot these data in a time-series graph. Based on the graph, what time-series components are present in the data?
b. Develop the seasonal indexes for each month. Describe what the seasonal index for August means.
c. Fit a linear trend model to the deseasonalized data for months 1 through 48 and determine the MAD value. Comment on the adequacy of the linear trend model based on these measures of forecast error.
d. Provide a seasonally unadjusted forecast using the linear trend model for each month of the year.
e. Use the seasonal index values computed in part b to provide seasonal adjusted forecasts for months 49 through 52.
Provide complete and step by step solution for the question and show calculations and use formulas.