A company forecasts next month’s demand by averaging the past three months’ actual sales. This approach is an example of:

Question

BlackTom AI · Accepted Answer

Question restatement: The scenario describes forecasting next month’s demand by taking the average of the past three months’ actual sales. This is a method used in time series forecasting.
Option 1: Naïve forecast. A naïve forecast typically projects that demand next period will be equal to demand in the most recent period. Since the method in question uses the average of three periods rather than just the last period, this is not naïve forecasting.
Option 2: Simple moving average. A simple moving average uses the unweighted average of the most recent k observations (here, k = 3) to forecast the next period. This exactly matches the described approach of averaging the past three months’ actual sales to forecast next month’s demand.
Option 3: Weighted moving average. A weighted moving average also uses the most recent observations, but assigns different weights to each period (e.g., more weight to recent months). The description did not mention weights or differential importance, only an equal average, so this does not fit.
Option 4: Exponential smoothing. Exponential smoothing generates forecasts by applying decreasing weights exponentially to past observations, rather than using a simple equal-average of the last three periods. Since the method described uses a straight average with equal consideration, exponential smoothing is not the correct characterization.
In summary, the method aligns with the concept of a straightforward average of a fixed number of recent observations, with no weighting or exponential adjustment, pointing to a simple moving average approach.

A company forecasts next month’s demand by averaging the past three months’ actual sales. This approach is an example of:单项选择题

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