Problem:
Errors that can be seen and measured are known as observation errors. These metrics were developed to track the discrepancy between measured and real values. These mistakes could be accidental or planned.
By optimizing the procedures, errors measures assist in observing and optimizing the error. The errors are predicted using a variety of techniques, including exponential smoothing and moving averages. In order to generate weighted moving averages, past data is given less weight than current statistics. By multiplying each price by the weighting factor, it is shown. In the exponential smoothing method, future forecasting is predicted using the smoothing constant.
Anderson, D. R., Sweeney, D. J., Williams, T. A., Camm, J. D., Cochran, J. L., Fry, M. J., & Ohlmann, J. W. (2016). Quantitative methods for business with CengageNOW (13th ed.). Boston, MA: Cengage Learning. ISBN-13: 9781305799257.