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相关概念视频

Probability in Statistics01:14

Probability in Statistics

14.7K
Probability is the likelihood of an event occurring. The term event is defined as a collection of results of a procedure. An event is a simple event when an outcome cannot be divided into simpler parts.
An example of a simple event is a coin toss. The result of a coin toss is either a head or a tail. Here, head and tail are two simple events. These two simple events make up the sample space. Further, the probability of an event occurring falls within the range of 0 to 1. The probability of an...
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Testing a Claim about Population Proportion01:24

Testing a Claim about Population Proportion

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A complete procedure for testing a claim about a population proportion is provided here.
There are two methods of testing a claim about a population proportion: (1) Using the sample proportion from the data where a binomial distribution is approximated to the normal distribution and (2) Using the binomial probabilities calculated from the data.
The first method uses normal distribution as an approximation to the binomial distribution. The requirements are as follows: sample size is large...
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Probability Laws01:49

Probability Laws

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Overview
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Binomial Probability Distribution01:15

Binomial Probability Distribution

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A binomial distribution is a probability distribution for a procedure with a fixed number of trials, where each trial can have only two outcomes.
The outcomes of a binomial experiment fit a binomial probability distribution. A statistical experiment can be classified as a binomial experiment if the following conditions are met:
There are a fixed number of trials. Think of trials as repetitions of an experiment. The letter n denotes the number of trials.
There are only two possible outcomes,...
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Hindsight Biases01:12

Hindsight Biases

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Hindsight bias leads you to believe that the event you just experienced was predictable, even though it really wasn’t. In other words, you knew all along that things would turn out the way they did. Can you relate this to the phrase "Hindsight is 20/20" now? 
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Probability Distributions01:32

Probability Distributions

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 The probability of a random variable x  is the likelihood of its occurrence. A probability distribution represents the probabilities of a random variable using a formula, graph, or table. There are two types of probability distribution– discrete probability distribution and continuous probability distribution.
A discrete probability distribution is a probability distribution of discrete random variables. It can be categorized into binomial probability distribution and Poisson...
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Updated: Sep 20, 2025

Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods
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Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods

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翻转条件:为什么我们可能在概率上错了

David Sidebotham1,2, Tim Dare3

  • 1Department of Anaesthesia and the Cardiothoracic and Vascular Intensive Care Unit, Auckland City Hospital, Auckland, New Zealand.

Paediatric anaesthesia
|May 28, 2025
PubMed
概括
此摘要是机器生成的。

翻转条件,这是条件概率的推理错误,导致误解诊断测试和法律证据. 了解这种谬论对于准确的医疗和法律决策至关重要.

关键词:
贝叶斯定理 贝叶斯定理认知偏见是一种认知偏见.可能性概率概率概率.这是检察官的谬论.统计作为一个主题.

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科学领域:

  • 统计 统计 统计 统计
  • 医学诊断 医学诊断 医学诊断
  • 法律理由 法律理由

背景情况:

  • 条件概率是评估事件概率的基础.
  • 条件概率中的错误,称为"翻转条件",可能会产生严重的后果.
  • 这种谬论经常遇到罕见事件和误解诊断测试.

研究的目的:

  • 定义和解释'翻转条件'的错误.
  • 为了说明这种错误如何导致误解诊断测试结果.
  • 讨论其在法律背景中的相关性,例如'检察官谬论',以现实世界的例子.

主要方法:

  • 条件概率的概念解释.
  • 在条件概率中转换术语时常见错误的分析.
  • 来自临床诊断和法律案件的说明性例子.

主要成果:

  • "翻转条件"发生在灵敏度与正预测值混时.
  • 这种错误有助于"检察官的谬论",混有罪的概率与证据的概率.
  • 这种谬论在处理罕见事件时尤为普遍.

结论:

  • 了解"翻转条件"对于准确解释医学测试至关重要.
  • 这种推理错误在法律程序中产生了重大影响,影响了统计证据的解释.
  • 意识到这种谬误可以防止司法失误,提高诊断准确度.