The forecasting method that uses a judgment factor to weigh the most recent data is

The forecasting method that uses a judgment factor to weigh the most recent data is

• A. Time-series
• B. Moving average
• C. Exponential smoothing
• D. Regression analysis

Answer: (C)

Exponential smoothing uses a smoothing constant to give more weight to the most recent observation. In the simplest form, the forecast for the next period blends the latest actual value with the previous forecast: F_next = alpha * X_now + (1 - alpha) * F_prev. The alpha parameter, between 0 and 1, acts as a judgment factor: a larger alpha makes the forecast respond quickly to new data, while a smaller alpha makes it more gradual. Older data still influence the forecast, but their impact decays exponentially as time passes. This approach contrasts with moving averages, which assign equal (or fixed) weights to values in a window, and with regression, which builds a model from multiple variables rather than weighting recent observations with a single smoothing constant. Time-series is a broad category that includes exponential smoothing as a specific method.

Exponential smoothing uses a smoothing constant to give more weight to the most recent observation. In the simplest form, the forecast for the next period blends the latest actual value with the previous forecast: F_next = alpha * X_now + (1 - alpha) * F_prev. The alpha parameter, between 0 and 1, acts as a judgment factor: a larger alpha makes the forecast respond quickly to new data, while a smaller alpha makes it more gradual. Older data still influence the forecast, but their impact decays exponentially as time passes.

This approach contrasts with moving averages, which assign equal (or fixed) weights to values in a window, and with regression, which builds a model from multiple variables rather than weighting recent observations with a single smoothing constant. Time-series is a broad category that includes exponential smoothing as a specific method.