Answer:
Step-by-step explanation:
Statement A: Increasing a moving average window will enhance noise dampening.
Statement B: Decreasing a moving average window will enhance impulse response.
Statement C: Increasing the smoothing constant in exponential smoothing will enhance impulse response.
Statement D: Decreasing the smoothing constant in exponential smoothing will enhance noise dampening.
Let's evaluate each statement:
A. Increasing a moving average window will enhance noise dampening.
This statement is true. Increasing the window size of a moving average smooths out the fluctuations in the data and reduces the effect of noise, thus enhancing noise dampening.
B. Decreasing a moving average window will enhance impulse response.
This statement is false. Decreasing the window size of a moving average reduces the number of data points considered, leading to less smoothing and a faster response to changes in the data. It does not enhance impulse response.
C. Increasing the smoothing constant in exponential smoothing will enhance impulse response.
This statement is false. Increasing the smoothing constant in exponential smoothing increases the weight given to more recent data points, which results in smoother and more stable forecasts. It does not enhance impulse response.
D. Decreasing the smoothing constant in exponential smoothing will enhance noise dampening.
This statement is true. Decreasing the smoothing constant in exponential smoothing gives more weight to past observations, which helps in reducing the impact of noise and enhances noise dampening.
Based on the evaluation, 2 out of the 4 statements are correct.