Q. 1. Explain how can trendless data be evaluated?

Explain 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, illustrate what type of smoothing constant should be chosen for little smoothing compared with moderate smoothing?

Justify your answers using examples and reasoning.

2. Explain how can forecasts improve communication in an organization?

Explain why do forecasts typically go wrong?

Illustrate 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.