A moving average model is a type of

A moving average model is a type of

• A. Time series forecasting method
• B. Qualitative forecasting method
• C. Causal model
• D. Judgmental forecasting

Answer: (A)

A moving average model is a time series forecasting method because it relies on sequential data points collected over time and uses past observations to predict the next value. It treats data as a time-ordered sequence and smooths out short-term fluctuations to reveal underlying patterns. This is a quantitative approach, not a qualitative judgment, not a causal model that links outcomes to external factors, and not a purely human-influenced forecast. In its simplest form, the forecast for the next period is the average of the most recent observations, which is exactly what defines a moving average within time series analysis.

A moving average model is a time series forecasting method because it relies on sequential data points collected over time and uses past observations to predict the next value. It treats data as a time-ordered sequence and smooths out short-term fluctuations to reveal underlying patterns. This is a quantitative approach, not a qualitative judgment, not a causal model that links outcomes to external factors, and not a purely human-influenced forecast. In its simplest form, the forecast for the next period is the average of the most recent observations, which is exactly what defines a moving average within time series analysis.