Question 1. How can trendless data be evaluated?
How does a trailing-moving average compare to a centered-moving average?
When should exponential smoothing be used for data? Explain with an example.
In exponential smoothing, what type of smoothing constant should be chosen for little smoothing compared with moderate smoothing?
Justify your answers using examples and reasoning.
Question 2. How can forecasts improve communication in an organization?
Why do forecasts typically go wrong?
What can a researcher do to increase the chances that a forecast will be effective?
Are more complicated forecasting models, such as autoregressive integrated moving average (ARIMA) and autoregressive (AR), typically better at forecasting than less complicated models? Explain.
Justify your answers using examples and reasoning.