Question1: Explain the concepts of bias and error in forecasting
1. what are they ?
2. how do we detect them?
3. What impact might they have on production?
Answer1:
1. Forecasting error is the differences between the actual result and the generated forecasts.
Errors could come from two sources. First, there are the usual errors similar to the standard
deviation of any set of data. Second, there are errors that arise because the data is mistake
and line is wrong.
Forecasting bias is the mean error of the forecasting errors. It means that the average
deviation between actual demand and forecast demand.
2. We could use the Actual data and Forecast data to detect the forecasting errors. (Both of the
data must be correct) Equation will be: Forecasting Error= Actual – Forecast .
Forecasting bias is the mean error of the forecasting errors. To measure the bias, the forecast
error in each period is actual demand in each period minus forecast demand for that period.
The Equation of bias: Bias=∑(𝐀𝐜𝐭𝐮𝐚𝐥 𝐃𝐞𝐦𝐚𝐧𝐝𝐢−𝐅𝐨𝐫𝐞𝐜𝐚𝐬𝐭 𝐃𝐞𝐦𝐚𝐧𝐝𝐢)
𝐧
𝐢=𝟏
𝐧
3. The method we use to forecast the demand should produce forecasts that are neither
consistently high nor consistently low. Forecasts should not be overly optimistic or
