The Role of Probability for Understanding Statistical Inference
Manfred Borovcnik
Abstract
Open-access reader
Manfred Borovcnik
Abstract
Open-access reader
Probability is the basis for intelligent actions and decisions in the face of uncertainty. That includes statistical inference as well as considerations of reliability, risk, and decision-making. Curricula have reduced approaches with respect to the nature of probability. With easy access to computer technology, simulation has become the predominant approach to teaching. Although simulation is an effective method to replace complicated mathematics, it reduces concepts to their frequentist part. This culminates in an approach to informal inference that makes probability and conditional probability redundant. However, the relevant properties of statistical inference require a comprehensive conception of probability to be shaped in the individual’s cognitive system.
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Probability is the basis for intelligent actions and decisions in the face of uncertainty. That includes statistical inference as well as considerations of reliability, risk, and decision-making. Curricula have reduced approaches with respect to the nature of probability. With easy access to computer technology, simulation has become the predominant approach to teaching. Although simulation is an effective method to replace complicated mathematics, it reduces concepts to their frequentist part. This culminates in an approach to informal inference that makes probability and conditional probability redundant. However, the relevant properties of statistical inference require a comprehensive conception of probability to be shaped in the individual’s cognitive system.
Key concepts: Frequentist inference, Statistical inference, Fiducial inference, Computer science, Inference, Frequentist probability, Conditional probability, Empirical probability