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相关概念视频

Accuracy and Precision01:52

Accuracy and Precision

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Scientists typically make repeated measurements of a quantity to ensure the quality of their findings and to evaluate both the precision and the accuracy of their results. Measurements are said to be precise if they yield very similar results when repeated in the same manner. A measurement is considered accurate if it yields a result that is very close to the true or the accepted value. Precise values agree with each other; accurate values agree with a true value.  Highly accurate...
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Uncertainty in Measurement: Accuracy and Precision03:37

Uncertainty in Measurement: Accuracy and Precision

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Scientists typically make repeated measurements of a quantity to ensure the quality of their findings and to evaluate both the precision and the accuracy of their results. Measurements are said to be precise if they yield very similar results when repeated in the same manner. A measurement is considered accurate if it yields a result that is very close to the true or the accepted value. Precise values agree with each other; accurate values agree with a true value. 
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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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Systematic Error: Methodological and Sampling Errors01:15

Systematic Error: Methodological and Sampling Errors

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In the case of systematic errors, the sources can be identified, and the errors can be subsequently minimized by addressing these sources. According to the source, systematic errors can be divided into sampling, instrumental, methodological, and personal errors.
Sampling errors originate from improper sampling methods or the wrong sample population. These errors can be minimized by refining the sampling strategy. Defective instruments or faulty calibrations are the sources of instrumental...
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Random and Systematic Errors

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Scientists always try their best to record measurements with the utmost accuracy and precision. However, sometimes errors do occur. These errors can be random or systematic. Random errors are observed due to the inconsistency or fluctuation in the measurement process, or variations in the quantity itself that is being measured. Such errors fluctuate from being greater than or less than the true value in repeated measurements. Consider a scientist measuring the length of an earthworm using a...
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相关实验视频

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Making Record-efficiency SnS Solar Cells by Thermal Evaporation and Atomic Layer Deposition
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为了更好的科学,更好的准确性. . . . . . . . . . . . . . . 这就是为什么. . . . . . . . . . . . . . . 这就是为什么. 通过随机的结论.

Clintin P Davis-Stober1, Jason Dana2, David Kellen3

  • 1Department of Psychological Sciences, MU Institute for Data Science and Informatics, University of Missouri.

Perspectives on psychological science : a journal of the Association for Psychological Science
|July 19, 2023
PubMed
概括
此摘要是机器生成的。

用小样本大小和微妙效应进行的研究可以产生像抛硬币一样随机的结果. 这挑战了传统的假设测试和统计功率计算,即使是真实效应.

关键词:
基准指标是指标的基准值.估计估计估计的估计.假设测试 测试 假设测试随机的结论 随机的结论 随机的结论测试 测试 测试 测试

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科学领域:

  • 心理学,神经科学和医学

背景情况:

  • 使用人类受试者的研究面临挑战,因为样本大小有限和经验效应小.
  • 这些局限性可能导致发现难以区分随机机会.

研究的目的:

  • 使用随机结论的概念,建立解释效果大小估计的基线.
  • 为测试假设和统计功率计算提出更严格的门.

主要方法:

  • 证明小样本研究结果的模式可能与随机结果无法区分.
  • 检查心理学,神经科学和医学近期的分析,以评估小效应的不可区分性.

主要成果:

  • 从小效应的研究中得出的结果几乎无法与随机结论区分.
  • 这种无法区分的情况即使是底层效应是真实的,也是如此.

结论:

  • 小样本研究的固有困难需要重新评估统计解释.
  • 需要更严格的假设测试和功率计算标准来考虑随机结果的可能性.