Question

Which of the following is not a characteristic of exponential smoothing?

1) Takes into account all past observations
2) Weights recent observations more heavily
3) Requires a smoothing constant
4) Uses a moving average

Answer 1

Option 4) Uses a moving average, is not a characteristic of exponential smoothing. Exponential smoothing applies weighted averages that decrease exponentially for past data and does not use a simple moving average.

Step-by-step explanation:

The student has asked which of the following is not a characteristic of exponential smoothing: 1) Takes into account all past observations, 2) Weights recent observations more heavily, 3) Requires a smoothing constant, 4) Uses a moving average.

Exponential smoothing is a forecasting technique used in time series data analysis. It addresses three out of the four options given. First, it does take into account all past observations. Secondly, recent observations are indeed weighted more heavily. Third, a smoothing constant, typically denoted by α (alpha), is required to determine the extent of the smoothing.

However, the technique does not use a moving average; instead, it calculates the forecasted values by applying weighted averages that decrease exponentially for past data. Therefore, option 4) Uses a moving average, is not a characteristic of exponential smoothing.