相关实验视频

Updated: Jun 27, 2025

Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments
13:00

Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments

Published on: January 23, 2017

9.9K

一种适应贝叶斯式方法,用于在联合监测平均值和方差时提高灵敏度,使用Max-EWMA控制图表

Abdullah A Zaagan1, Muhammad Noor-Ul-Amin2, Imad Khan3

  • 1Department of Mathematics, Faculty of Science, Jazan University, P.O. Box 2097, Jazan, 45142, Kingdom of Saudi Arabia.

Scientific reports
|April 30, 2024
PubMed
概括

本研究引入了适应贝叶斯马克斯-EWMA控制图,用于增强过程监控. 适应性方法提高了检测过程平均值和方程差异变化的灵敏度.

关键词:
适应性最大-EWMA 适应性运行时间的平均长度.贝叶斯的方法是贝叶斯的方法.控制图表中的控制图表.联合监督 联合监督 联合监督蒙特卡洛模拟的蒙特卡洛模拟

更多相关视频

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach04:35

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach

Published on: July 3, 2020

3.3K
Semi-Automated Analysis of Peak Amplitude and Latency for Auditory Brainstem Response Waveforms Using R06:01

Semi-Automated Analysis of Peak Amplitude and Latency for Auditory Brainstem Response Waveforms Using R

Published on: December 9, 2022

2.5K

相关概念视频

Standard Error of the Mean01:13

Standard Error of the Mean

The sampling variability of a statistic is defined as how much the statistic varies from one sample to another. The sampling variability of a statistic is typically measured by measuring its standard error.
The standard error of the mean is an example of a standard error. It is a unique standard deviation known as the standard deviation of the sampling distribution of the mean. The standard error of the mean is a statistic that calculates how correctly a sample distribution represents a...
5.8K
Empirical Method to Interpret Standard Deviation01:09

Empirical Method to Interpret Standard Deviation

The empirical rule, also known as the three-sigma rule, allows a statistician to interpret the standard deviation in a normally distributed dataset. The rule states that 68% of the data lies within one standard deviation from the mean, 95% lies within two standard deviations from the mean, and 99.7% lies within three standard deviations from the mean. Additionally, this rule is also called the 68-95-99.7 rule.
This rule is used widely in statistics to calculate the proportion of data values...
5.2K
Estimating Population Mean with Unknown Standard Deviation01:22

Estimating Population Mean with Unknown Standard Deviation

In practice, we rarely know the population standard deviation. In the past, when the sample size was large, this did not present a problem to statisticians. They used the sample standard deviation s as an estimate for σ and proceeded as before to calculate a confidence interval with close enough results. However, statisticians ran into problems when the sample size was small. A small sample size caused inaccuracies in the confidence interval.
William S. Gosset (1876–1937) of the...
7.7K
Mean Absolute Deviation01:13

Mean Absolute Deviation

The mean absolute deviation is also a measure of the variability of data in a sample. It is the absolute value of the average difference between the data values and the mean.
Let us consider a dataset containing the number of unsold cupcakes in five shops: 10, 15, 8, 7, and 10. Initially, calculate the sample mean. Then calculate the deviation, or the difference, between each data value and the mean. Next, the absolute values of these deviations are added and divided by the sample size to...
2.6K
Estimating Population Mean with Known Standard Deviation01:16

Estimating Population Mean with Known Standard Deviation

To construct a confidence interval for a single unknown population mean μ, where the population standard deviation is known, we need sample mean as an estimate for μ and we need the margin of error. Here, the margin of error (EBM) is called the error bound for a population mean (abbreviated EBM). The sample mean is the point estimate of the unknown population mean μ.
The confidence interval estimate will have the form as follows:
(point estimate - error bound, point estimate +...
8.3K
Regression Toward the Mean01:52

Regression Toward the Mean

Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when...
6.3K