基本概率运算:概率推理的框架

IF 2.5 3区 心理学 Q2 PSYCHOLOGY, EXPERIMENTAL
Siegfried Macho, Thomas Ledermann
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引用次数: 0

摘要

初等概率运算框架解释了初等概率推理任务的结构以及人们在这些任务中的表现。该框架包括三个部分:(a)三种类型的概率:联合概率、边际概率和条件概率;(b)三种基本概率操作:组合、边缘化和条件作用,以及(c)实现EPO的定量推理模式。EPO框架的正式部分是一个计算级理论,它提供了一个基于解决问题的计算需求的问题空间表示和基本概率问题的分类。根据EPO框架,目前改进概率推理的方法有两种:第一,将贝叶斯问题简化为一种需要较少概念和程序能力的概率问题。第二,通过培养定量推理图式的应用,提高人们的运用能力。该方法提出了新的应用,包括概率推理的教学,在概率推理中使用类比问题解决,以及在概率问题解决中分析错误的新方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Elementary probabilistic operations: a framework for probabilistic reasoning
The framework of elementary probabilistic operations (EPO) explains the structure of elementary probabilistic reasoning tasks as well as people’s performance on these tasks. The framework comprises three components: (a) Three types of probabilities: joint, marginal, and conditional probabilities; (b) three elementary probabilistic operations: combination, marginalization, and conditioning, and (c) quantitative inference schemas implementing the EPO. The formal part of the EPO framework is a computational level theory that provides a problem space representation and a classification of elementary probabilistic problems based on computational requirements for solving a problem. According to the EPO framework, current methods for improving probabilistic reasoning are of two kinds: First, reduction of Bayesian problems to a type of probabilistic problems requiring less conceptual and procedural competencies. Second, enhancing people’s utilization competence by fostering the application of quantitative inference schemas. The approach suggests new applications, including the teaching of probabilistic reasoning, using analogical problem solving in probabilistic reasoning, and new methods for analyzing errors in probabilistic problem solving.
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来源期刊
Thinking & Reasoning
Thinking & Reasoning PSYCHOLOGY, EXPERIMENTAL-
CiteScore
6.50
自引率
11.50%
发文量
25
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