Abstract
The statistical methods that we have discussed so far are known as frequentist (or classical) methods. The frequentist point of view is based on the following postulates:
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F1
Probability refers to limiting relative frequencies. Probabilities are objective properties of the real world.
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F2
Parameters are fixed, unknown constants. Because they are not fluctuating, no useful probability statements can be made about parameters.
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F3
Statistical procedures should be designed to have well-defined long run frequency properties. For example, a 95 percent confidence interval should trap the true value of the parameter with limiting frequency at least 95 percent.
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© 2004 Springer Science+Business Media New York
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Wasserman, L. (2004). Bayesian Inference. In: All of Statistics. Springer Texts in Statistics. Springer, New York, NY. https://doi.org/10.1007/978-0-387-21736-9_11
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DOI: https://doi.org/10.1007/978-0-387-21736-9_11
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