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相关概念视频

Bootstrapping01:24

Bootstrapping

577
The term "bootstrap" originated in the 19th century as a metaphor for self-improvement or achieving something independently, without external assistance. This concept extends to statistical bootstrapping, a self-contained method for estimating population parameters through resampling, even though it can be computationally intensive. Developed by the American statistician Dr. Bradley Efron in 1979, bootstrapping provides a robust way to perform inference when the original sample size is...
577
Percentile01:18

Percentile

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A percentile indicates the relative standing of a data value when data are sorted into numerical order from smallest to largest. It represents the percentages of data values that are less than or equal to the pth percentile. For example, 15% of data values are less than or equal to the 15th percentile.
6.5K
Modified Boxplots00:57

Modified Boxplots

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A standard box and whisker plot informs us about the spread of the data in a given sample. One can identify the minimum value, maximum value, first quartile value, second quartile or median value, and third quartile.
However, the box plot does not tell the reader about outliers - values that lie far from the center of the data. We can modify the standard box and whisker plot to identify the outliers and visualize the actual spread of the data in a sample.
Initially, we calculate the adjusted...
9.1K
Finding Critical Values for Chi-Square01:18

Finding Critical Values for Chi-Square

2.9K
Consider a curve representing sample data drawn randomly from a normally distributed population. One must construct confidence intervals to estimate or to test a claim regarding the population standard deviation. For example, a 95% confidence interval covers 95% of the area under the curve, and the remaining 5% is equally distributed on either side of the curve. To achieve such confidence intervals, one must determine the critical values. The critical values are simply the values separating the...
2.9K
Interpreting R Charts01:22

Interpreting R Charts

49
R chart, or range chart, is a fundamental tool in statistical process control used to monitor the variability within a process. It complements the X-bar (x̄) chart by focusing on the range of the data, rather than individual values, providing a clear picture of the process dispersion over time.
An R chart plots the range of subsets of measurements collected from a process. Each point on the chart represents the range—defined as the difference between the maximum and minimum...
49
Distributions to Estimate Population Parameter01:26

Distributions to Estimate Population Parameter

4.0K
The accurate values of population parameters such as population proportion, population mean, and population standard deviation (or variance) are usually unknown. These are fixed values that can only be estimated from the data collected from the samples. The estimates of each of these parameters are sample proportion, the sample mean, and sample standard deviation (or variance). To obtain the values of these sample statistics, data are required that have particular distribution and central...
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相关实验视频

Updated: May 29, 2025

An R-Based Landscape Validation of a Competing Risk Model
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An R-Based Landscape Validation of a Competing Risk Model

Published on: September 16, 2022

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林德利几何百分位数的参数引导控制图.

Muthanna Ali Hussein Al-Lami1,2, Hossein Jabbari Khamnei1, Ali Akbar Heydari1

  • 1Department of Statistics, Faculty of Mathematics, Statistics and Computer Science, University of Tabriz, Tabriz, Iran.

PloS one
|February 6, 2025
PubMed
概括

本研究引入了一种新的控制图表,用于监测偏差数据,特别是林德利几何 (LG) 分布. 参数启动方法通过在工业环境中有效跟踪LG分布百分位来提高质量控制.

科学领域:

  • 工业工程 工业工程 工业工程
  • 统计质量控制 统计质量控制
  • 可靠性工程可靠性工程

背景情况:

  • 传统的控制图表 (例如,Shewhart图表) 对于像林德利几何分布 (LG) 这样的倾斜分布往往是不够的.
  • 在建模材料强度和故障时,LG分布至关重要,特别是在结构设计中,较低的百分位数意味着拉伸强度降低.

研究的目的:

  • 开发和评估一个新的控制图,使用参数启动技术来监测LG分布的百分点.
  • 为显示偏斜分布的过程提供更有效的质量控制方法.

主要方法:

  • 进行了广泛的模拟,以评估拟议的控制图表的性能.
  • 该研究考虑了各种因素,包括LG分布参数,百分位数值,I型错误率和样本大小.

主要成果:

  • 新的控制图表显示了对LG分布参数变化的高度敏感性和不同百分位数的一致性.
  • 研究结果表明,子组大小,百分位数选择和显著性水平显著影响控制极限,强调需要仔细选择参数.

结论:

  • 拟议的控制图为涉及LG分销的工业质量控制应用提供了强大而实用的解决方案.
  • 建议在现实生产环境中进行进一步的研究,以验证其效率和可靠性.

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