Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Sign Test for Median of Single Population01:20

Sign Test for Median of Single Population

181
In general, the sign test serves as a nonparametric method to test hypotheses about the median of a single population when the data does not follow a known distribution. This simplicity makes it particularly useful for small sample sizes or when the assumptions of parametric tests cannot be met. The process begins with identifying a null hypothesis, typically stating that the population median equals a specific value. The alternative hypothesis could be that the median is either not equal to,...
181
Median01:08

Median

19.9K
Besides mean, the median is a widely used measure of central tendency. Typically, median is defined as the central or middle value of a data set, measured by arranging the data elements in an increasing or decreasing order. Since this middle value is not affected by the precise numerical values of the outliers or fluctuations, it is insensitive to them. Hence, in cases where a data set may have outliers or the extreme values are not known, the median is a better measure of the central tendency...
19.9K
Wilcoxon Signed-Ranks Test for Median of Single Population01:14

Wilcoxon Signed-Ranks Test for Median of Single Population

223
The Wilcoxon signed-rank test for the median of a single population is a nonparametric test used to evaluate whether the median of a population differs from a specified value. Unlike parametric tests, it does not require data to follow a normal distribution, making it suitable for non-normal or small samples. The test begins by calculating the difference (d) between each observation and the hypothesized median. The absolute values of these differences are ranked in ascending order, with ties...
223
One-Way ANOVA: Equal Sample Sizes01:15

One-Way ANOVA: Equal Sample Sizes

3.5K
One-Way ANOVA can be performed on three or more samples with equal or unequal sample sizes. When one-way ANOVA is performed on two datasets with samples of equal sizes, it can be easily observed that the computed F statistic is highly sensitive to the sample mean.
Different sample means can result in different values for the variance estimate: variance between samples. This is because the variance between samples is calculated as the product of the sample size and the variance between the...
3.5K
One-Way ANOVA: Unequal Sample Sizes01:15

One-Way ANOVA: Unequal Sample Sizes

5.9K
One-way ANOVA can be performed on three or more samples of unequal sizes. However, calculations get complicated when sample sizes are not always the same. So, while performing ANOVA with unequal samples size, the following equation is used:
5.9K
Measures of Central Tendency02:16

Measures of Central Tendency

16.2K
The "center" of a data set is also a way of describing location. The two most widely used measures of the "center" of the data are the mean (average) and the median. The words "mean" and "average" are often used interchangeably. The substitution of one word for the other is common practice. The technical term is "arithmetic mean" and "average" is technically a center location. However, in practice among non-statisticians,...
16.2K

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

A Novel Conditional Adra2a-Knockout Mouse Line Reveals Cell-specific Contributions to Specific Dimensions of Sedation.

bioRxiv : the preprint server for biology·2026
Same author

A catecholamine-independent pathway controlling adaptive adipocyte lipolysis.

Nature metabolism·2026
Same author

Central activation of catecholamine-independent lipolysis drives the end-stage catabolism of all adipose tissues.

bioRxiv : the preprint server for biology·2024
Same author

Norepinephrine Neurons in the Nucleus of the Solitary Tract Suppress Luteinizing Hormone Secretion in Female Mice.

The Journal of neuroscience : the official journal of the Society for Neuroscience·2024
Same author

Norepinephrine Drives Sleep Fragmentation Activation of Asparagine Endopeptidase, Locus Ceruleus Degeneration, and Hippocampal Amyloid-β<sub>42</sub> Accumulation.

The Journal of neuroscience : the official journal of the Society for Neuroscience·2024
Same author

Endothelial MEKK3-KLF2/4 signaling integrates inflammatory and hemodynamic signals during definitive hematopoiesis.

Blood·2022

相关实验视频

Updated: Sep 11, 2025

An Unbiased Approach of Sampling TEM Sections in Neuroscience
10:56

An Unbiased Approach of Sampling TEM Sections in Neuroscience

Published on: April 13, 2019

7.3K

对于偶数样本大小的单一无偏差中位数溶液.

Mikhail Y Lipin1, Elias Benjamin Crampton2, Steven A Thomas1

  • 1Department of Pharmacology, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.

bioRxiv : the preprint server for biology
|August 13, 2025
PubMed
概括

研究人员开发了一种对具有均样本大小的生物数据的公正中位数估计器. 这种新的中位数比传统的中位数更准确,差异较小,特别是在不对称分布中.

科学领域:

  • 统计建模 统计建模
  • 实验生物学中的强有力的估计.

背景情况:

  • 实验生物学数据通常包含异常值和不对称分布.
  • 中位数是衡量中心趋势的可靠指标,与平均值相比,异常值的影响要小.
  • 传统的中位数计算可以在有偶数观测的数据集中引入偏差,假设数据对称.

研究的目的:

  • 识别和导出对排序数据集的公正中位数估计器.
  • 为了解决传统中位数在偶数样本大小的不对称分布中引入的偏差.

主要方法:

  • 通过最小化提升到接近1的理数次数的余数和来得出一个无偏差的中位数估计器.
  • 使用Poisson分布式数据集,比较了公正和常规中位数的属性.
  • 在IgorPro软件中使用Mersenne Twister算法生成随机样本.

主要成果:

  • 对于奇数样本大小,无偏差中位数与常规中位数相同.
  • 对于偶数样本大小,无偏差中位数等同于上面和下面的数据点距离的乘积,不同于非对称分布中的常规中位数.
  • 两位估计者都低估了Poisson数据的平均值,但公正的中位数始终接近预期值,并且显示出较低的差异.

结论:

关键词:
鱼鱼是什么意思 鱼是什么意思不偏向的中位数.问题是很好地提出的问题.

更多相关视频

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

7.6K
Using the Race Model Inequality to Quantify Behavioral Multisensory Integration Effects
08:13

Using the Race Model Inequality to Quantify Behavioral Multisensory Integration Effects

Published on: May 10, 2019

6.5K

相关实验视频

Last Updated: Sep 11, 2025

An Unbiased Approach of Sampling TEM Sections in Neuroscience
10:56

An Unbiased Approach of Sampling TEM Sections in Neuroscience

Published on: April 13, 2019

7.3K
Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

7.6K
Using the Race Model Inequality to Quantify Behavioral Multisensory Integration Effects
08:13

Using the Race Model Inequality to Quantify Behavioral Multisensory Integration Effects

Published on: May 10, 2019

6.5K
  • 提出的无偏差中位数估计器更准确,并且与偶数样本大小的常规中位数相比,其差异较小.
  • 这种无偏差的中位数为不对称的生物数据提供了中心趋势的优越度量.
  • 这些发现为分析容易出现异常值和不对称的生物数据集提供了更强大的统计工具.