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Significant Figures in Calculations00:58

Significant Figures in Calculations

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Uncertainty in measurements can be avoided by reporting the results of a calculation with the correct number of significant figures. This can be determined by the following rules for rounding numbers:
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Proofreading01:43

Proofreading

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Overview
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Detection of Gross Error: The Q Test01:00

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When one or more data points appear far from the rest of the data, there is a need to determine whether they are outliers and whether they should be eliminated from the data set to ensure an accurate representation of the measured value. In many cases, outliers arise from gross errors (or human errors) and do not accurately reflect the underlying phenomenon. In some cases, however, these apparent outliers reflect true phenomenological differences. In these cases, we can use statistical methods...
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Accuracy and Errors in Hypothesis Testing01:13

Accuracy and Errors in Hypothesis Testing

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Hypothesis testing is a fundamental statistical tool that begins with the assumption that the null hypothesis H0 is true. During this process, two types of errors can occur: Type I and Type II. A Type I error refers to the incorrect rejection of a true null hypothesis, while a Type II error involves the failure to reject a false null hypothesis.
In hypothesis testing, the probability of making a Type I error, denoted as α, is commonly set at 0.05. This significance level indicates a 5%...
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Numerical Calculations01:24

Numerical Calculations

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In engineering applications, the representation of the numerical value is critical. Presenting or reporting the answer is one of the essential parts of engineering practices. Numerical calculations are performed using handheld calculators or computers since numerically accurate answers are always preferred.
The solution to a problem is obtained using different methods. While manually solving algebraic symbols is one of the most common methods, the graphical method is often preferred. Computers...
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Propagation of Uncertainty from Random Error00:59

Propagation of Uncertainty from Random Error

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An experiment often consists of more than a single step. In this case, measurements at each step give rise to uncertainty. Because the measurements occur in successive steps, the uncertainty in one step necessarily contributes to that in the subsequent step. As we perform statistical analysis on these types of experiments, we must learn to account for the propagation of uncertainty from one step to the next. The propagation of uncertainty depends on the type of arithmetic operation performed on...
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在数学同行评审中检查正确性.

Christian Greiffenhagen1,2

  • 1The Hong Kong Polytechnic University, Hong Kong, China.

Social studies of science
|September 30, 2023
PubMed
概括

数学同行评审虽然不能保证正确性,但被数学家们重视,因为它为证明增加了确定性. 结果的接受也取决于社区的共识和时间,而不仅仅是最初的出版.

科学领域:

  • 数学 数学 是一个数学.
  • 学术传播学术交流

背景情况:

  • 数学依赖于演证明,与实证自然科学不同.
  • 尽管具有可复制性的理想,但数学文献中存在错误.
  • 验证数学证明是复杂和具有挑战性的.

研究的目的:

  • 调查同行评审在数学中的作用和看法.
  • 了解数学家如何评估公布结果的正确性和确定性.

主要方法:

  • 分析了95次与数学期刊编辑进行的定性访谈.
  • 审查了100多份裁判报告和同行评审通信.

主要成果:

  • 数学家承认,同行评审并不能保证正确性,但仍将其作为增加确定性的价值.
  • 在同行评审期间,关于证据的有效性和意义的意见分歧会出现.
  • 社区接受和时间对于验证数学结果至关重要,超出初始同行评审.

结论:

  • 数学中的同行评审提供了一个有价值的审查层,增强对结果的信心.
  • 数学界在确定证明的有效性和接受性方面发挥着至关重要的作用.
  • 在同行评审期刊上发表是必要的,但不足以充分接受数学发现的步骤.
关键词:
确定性 确定性 确定性这是一个错误的错误错误.数学数学就是一个数学.在同行评审中进行同行评审.证明证明证明证明证明复制复制复制复制复制复制复制科学界的科学社区.

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