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相关概念视频

Uncertainty in Measurement: Accuracy and Precision03:37

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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 Precision01:52

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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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Residuals and Least-Squares Property01:11

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The vertical distance between the actual value of y and the estimated value of y. In other words, it measures the vertical distance between the actual data point and the predicted point on the line
If the observed data point lies above the line, the residual is positive, and the line underestimates the actual data value for y. If the observed data point lies below the line, the residual is negative, and the line overestimates the actual data value for y.
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When we take repeated measurements on the same or replicated samples, we will observe inconsistencies in the magnitude. These inconsistencies are called errors. To categorize and characterize these results and their errors, the researcher can use statistical analysis to determine the quality of the measurements and/or suitability of the methods.
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In any measurement, the precision of the measuring tool is an essential factor. An ordinary ruler, for example, can measure length to the closest millimeter; a caliper, on the other hand, can measure length to the nearest 0.01 mm. As a result, the caliper is a more precise measurement tool because it can measure extremely minute changes in length. The measurements will be more accurate if the measuring tool is more precise.
It should be emphasized that when we represent measured values, the...
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Counting is the type of measurement that is free from uncertainty, provided the number of objects being counted does not change during the process. Such measurements result in exact numbers. By counting the eggs in a carton, for instance, one can determine exactly how many eggs are there in the carton. Similarly, the numbers of defined quantities are also exact. For example, 1 foot is exactly 12 inches, 1 inch is exactly 2.54 centimeters, and 1 gram is exactly 0.001 kilograms. Quantities...
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从回归的角度了解测量精度.

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科学领域:

  • 心理测量 心理测量 心理测量
  • 统计建模 统计建模
  • 测量理论 测量理论

背景情况:

  • 现有的测量精度框架往往侧重于单独的可靠性或预测.
  • 麦当劳 (2011) 的回归框架为统一这些观点提供了基础.
  • 整合可靠性 (观察得分准确性) 和预测 (隐性得分估计) 对于全面的测量评估至关重要.

研究的目的:

  • 为了扩展麦当劳 (2011) 测量精度回归框架.
  • 整合可靠性和平均平方误差 (PRMSE) 的比例降低概念.
  • 引入和验证用于估计这些精度指标的蒙特卡洛 (MC) 方法.

主要方法:

  • 采用和扩展测量精度的回归框架.
  • 将观察到的分数分解为真分数和可靠性的错误.
  • 将潜伏得分分解为最佳预测指标 (EAP得分) 和PRMSE的预测错误.
  • 当分析解决方案复杂或不可用时,利用蒙特卡洛模拟进行估计.

主要成果:

  • 可靠性和PRMSE被证明是同态回归中的确定系数.
  • 蒙特卡洛方法被证明是估计可靠性和PRMSE的可行方法.
  • 提供了因子分析,双参数物流模型和二维项目响应树模型的插图.

结论:

  • 扩展回归框架为测量精度提供了统一的方法.
  • 蒙特卡洛方法提供了一种灵活的工具,用于在各种统计模型中估计可靠性和PRMSE.
  • 这项工作增强了在复杂的心理测量和统计背景下测量精度的理解和应用.