Why Use a Biased Estimator?

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SUMMARY

The discussion centers on the use of biased estimators in statistical analysis, highlighting that while biased estimators yield sample statistics that differ from population statistics, they can be necessary in practical scenarios. Specifically, many sensors produce biased measurements, necessitating the incorporation of bias estimation in models to achieve more accurate results. Ultimately, the consensus is that biased estimators are not preferred but may be the only option available in certain situations.

PREREQUISITES
  • Understanding of biased and unbiased estimators
  • Familiarity with statistical modeling techniques
  • Knowledge of sensor measurement principles
  • Basic grasp of estimation theory
NEXT STEPS
  • Research methods for correcting bias in sensor measurements
  • Explore statistical modeling techniques that incorporate bias estimation
  • Learn about the implications of using biased estimators in data analysis
  • Investigate case studies where biased estimators were effectively utilized
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Statisticians, data scientists, and engineers working with sensor data who need to understand the implications of using biased estimators in their analyses.

thrillhouse86
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Hey All,

I am comfortable with the idea of biased and unbiased estimators, but what I don't understand is why you would ever want to use a biased estimator ? at the end of the day doesn't it mean that the sample statistic is different from the population statistic you are trying to estimate ?
 
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thrillhouse86 said:
but what I don't understand is why you would ever want to use a biased estimator ?
The simple answer is that the biased estimator might be all you have available. Lots of sensors yield biased measurements. The sensor model had better include an estimation of the bias to yield an answer closer to the truth than that produced directly by the sensor.
 
So does that mean you never really want a biased estimator, but sometimes practical issues force you to work with one ?
 
Exactly.
 
cool thanks D H
 

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