The Need for a Standard for Making Predictions
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Elart von Collani
Abstract
In the last issue of EQC the “Guide to the Expression of Uncertainty in Measurement” (GUM) was critically discussed and it was shown that it is obsolete and should be replaced by a standard defining the rules for stochastic measurement procedures that in contrast to the GUM would express the inherent measurement uncertainty in an objective way, thus making reliable and accurate measurement procedures possible.
Closely connected to stochastic measurement procedures are stochastic prediction procedures, as any measurement procedure is based on a corresponding prediction procedure. Furthermore, prediction procedures play a central role in any decision-making process. Prediction procedures are therefore the most important tool for human individuals as well as for the human community for solving problems and being able to survive.
Having this in mind, mankind should be expected in its long history to have developed prediction procedures that, in an objective way, enable to look at the indeterminate future to prevent the occurrence of problems and to solve problems once they have occurred. Unfortunately, this is not the case. The technology of making predictions has not at all improved since the antiquity.
In this paper, predictions procedures are dealt with, and the development of a prediction standard for the protection against misleading or even fraudulent prediction is proposed.
© Heldermann Verlag
Articles in the same Issue
- Stochastic Measurement Procedures Based on Stationary Time Series
- Semi-Parametric Estimation of PX,Y (X > Y)
- On The Performance of A New Test of Exponentiality Against IFR Alternatives Based on the L-statistic Approach
- Control Chart for Autocorrelated Processes with Heavy Tailed Distributions
- Designing the Scale Counting Procedure for Large Numbers of Small Parts
- MTBF for K-out-of-N: G Systems with M Failure Modes
- Non-parametric Control Chart for Controlling Variability Based on Rank Test
- Bounds for Distorted Risk Measures
- Parameter Estimation for the Bivariate Exponential Distribution by the EM Algorithm Based on Censored Samples
- Explicit Expressions for Moments of Log Normal Order Statistics
- Partially Specified Prior
- The Need for a Standard for Making Predictions
Articles in the same Issue
- Stochastic Measurement Procedures Based on Stationary Time Series
- Semi-Parametric Estimation of PX,Y (X > Y)
- On The Performance of A New Test of Exponentiality Against IFR Alternatives Based on the L-statistic Approach
- Control Chart for Autocorrelated Processes with Heavy Tailed Distributions
- Designing the Scale Counting Procedure for Large Numbers of Small Parts
- MTBF for K-out-of-N: G Systems with M Failure Modes
- Non-parametric Control Chart for Controlling Variability Based on Rank Test
- Bounds for Distorted Risk Measures
- Parameter Estimation for the Bivariate Exponential Distribution by the EM Algorithm Based on Censored Samples
- Explicit Expressions for Moments of Log Normal Order Statistics
- Partially Specified Prior
- The Need for a Standard for Making Predictions
