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6. Point Estimation

Summary

Point estimation refers to the process of estimating a parameter from a probability distribution, based on observed data from the distribution. It is one of the core topics in mathematical statistics. In this chapter, we will explore the most common methods of point estimation: the method of moments, the method of maximum likelihood, and Bayes' estimators. We also study important properties of estimators, including sufficiency and completeness, and the basic question of whether an estimator is the best possible one.

Topics

  1. Estimators
  2. The Method of Moments
  3. Maximum Likelihood
  4. Bayes Estimators
  5. Best Unbiased Estimators
  6. Sufficient, Complete and Ancillary Statistics

Apps

Sources and Resources

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