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In simple exponential smoothing forecasting, to give higher weightage to recent demand information, the smoothing constant must be close to
- a)-1
- b)zero
- c)0.5
- d)1
Correct answer is option 'D'. Can you explain this answer?
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Verified Answer
In simple exponential smoothing forecasting, to give higher weightage ...
Value of α close to one have less of a smoothing effect and give greater weight to recent changes in the data.
Most Upvoted Answer
In simple exponential smoothing forecasting, to give higher weightage ...
Explanation:
Simple exponential smoothing is a forecasting technique that assigns different weights to past demand information based on a smoothing constant. The smoothing constant, also known as the alpha value, determines the weight given to the most recent demand information.
The formula for simple exponential smoothing is:
Forecast(t+1) = alpha * Demand(t) + (1 - alpha) * Forecast(t)
Here, the alpha value is the smoothing constant, which ranges from 0 to 1. A higher alpha value gives more weight to recent demand information, while a lower alpha value gives more weight to historical demand information.
Effect of the Smoothing Constant:
The smoothing constant determines the trade-off between the weight given to recent demand information and the weight given to historical demand information.
When the smoothing constant is close to 0, the forecast is mainly based on historical demand information. In this case, the forecast will be more stable and less responsive to recent changes in demand. This is because the weight given to recent demand information is very low.
On the other hand, when the smoothing constant is close to 1, the forecast is primarily based on the most recent demand information. In this case, the forecast will be more responsive to recent changes in demand, but it may also be more volatile. This is because the weight given to recent demand information is very high.
Optimal Smoothing Constant:
To give higher weightage to recent demand information, the smoothing constant must be close to 1. This means that a value of 1 will give the highest weight to the most recent demand information.
By setting the smoothing constant to 1, the forecast will be primarily based on the most recent demand information, making it more responsive to recent changes in demand. This is useful when there are significant fluctuations in demand and recent information is more relevant for forecasting.
Therefore, the correct answer is option 'D' - 1.
Simple exponential smoothing is a forecasting technique that assigns different weights to past demand information based on a smoothing constant. The smoothing constant, also known as the alpha value, determines the weight given to the most recent demand information.
The formula for simple exponential smoothing is:
Forecast(t+1) = alpha * Demand(t) + (1 - alpha) * Forecast(t)
Here, the alpha value is the smoothing constant, which ranges from 0 to 1. A higher alpha value gives more weight to recent demand information, while a lower alpha value gives more weight to historical demand information.
Effect of the Smoothing Constant:
The smoothing constant determines the trade-off between the weight given to recent demand information and the weight given to historical demand information.
When the smoothing constant is close to 0, the forecast is mainly based on historical demand information. In this case, the forecast will be more stable and less responsive to recent changes in demand. This is because the weight given to recent demand information is very low.
On the other hand, when the smoothing constant is close to 1, the forecast is primarily based on the most recent demand information. In this case, the forecast will be more responsive to recent changes in demand, but it may also be more volatile. This is because the weight given to recent demand information is very high.
Optimal Smoothing Constant:
To give higher weightage to recent demand information, the smoothing constant must be close to 1. This means that a value of 1 will give the highest weight to the most recent demand information.
By setting the smoothing constant to 1, the forecast will be primarily based on the most recent demand information, making it more responsive to recent changes in demand. This is useful when there are significant fluctuations in demand and recent information is more relevant for forecasting.
Therefore, the correct answer is option 'D' - 1.
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In simple exponential smoothing forecasting, to give higher weightage to recentdemand information, the smoothing constant must be close toa)-1b)zeroc)0.5d)1Correct answer is option 'D'. Can you explain this answer?
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