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

Estimating Population Mean with Unknown Standard Deviation01:22

Estimating Population Mean with Unknown Standard Deviation

8.8K
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...
8.8K
Estimating Population Standard Deviation01:26

Estimating Population Standard Deviation

3.3K
When the population standard deviation is unknown and the sample size is large, the sample standard deviation s is commonly used as a point estimate of σ. However, it can sometimes under or overestimate the population standard deviation. To overcome this drawback, confidence intervals are determined to estimate population parameters and eliminate any calculation bias accurately. However, this only applies to random samples from normally distributed populations. Knowing the sample mean and...
3.3K
Estimating Population Mean with Known Standard Deviation01:16

Estimating Population Mean with Known Standard Deviation

9.6K
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 +...
9.6K
Distributions to Estimate Population Parameter01:26

Distributions to Estimate Population Parameter

5.0K
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...
5.0K
Expected Frequencies in Goodness-of-Fit Tests01:19

Expected Frequencies in Goodness-of-Fit Tests

7.2K
A goodness-of-fit test is conducted to determine whether the observed frequency values are statistically similar to the frequencies expected for the dataset. Suppose the expected frequencies for a dataset are equal such as when predicting the frequency of any number appearing when casting a die. In that case, the expected frequency is the ratio of the total number of observations (n)  to the number of categories (k).
7.2K
One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation01:24

One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation

1.1K
This lesson introduces two critical methods in pharmacokinetics, the Wagner-Nelson and Loo-Riegelman methods, used for estimating the absorption rate constant (ka) for drugs administered via non-intravenous routes. The Wagner-Nelson method relates ka to the plasma concentration derived from the slope of a semilog percent unabsorbed time plot. However, it is limited to drugs with one-compartment kinetics and can be impacted by factors like gastrointestinal motility or enzymatic degradation.
On...
1.1K

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

Fast efficient coding and sensory adaptation in gain-adaptive recurrent networks.

Nature communications·2026
Same author

Human-level learning of complex novel tasks as theory-based modelling, exploration and planning.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences·2026
Same author

Artificial intelligence for science: The easy and hard problems.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences·2026
Same author

Endogenous precision of the number sense.

eLife·2026
Same author

Reconciling time and prediction error theories of associative learning.

Nature communications·2025
Same author

Quantifying the Cost of Context Sensitivity in Decision-Making.

Topics in cognitive science·2025
Same journal

Confident judgments of (mis)information veracity are more, rather than less, accurate.

PNAS nexus·2026
Same journal

Can AI help reduce prejudice? Evaluating the effectiveness of AI-powered personalized persuasion on support for transgender rights.

PNAS nexus·2026
Same journal

A cultural explanation for parole decisions in the United States.

PNAS nexus·2026
Same journal

A transformer-based language model reveals developmental constraint and network complexity during zebrafish embryogenesis.

PNAS nexus·2026
Same journal

Dual phosphoregulatory mechanisms of condensin I revealed by biochemical reconstitution.

PNAS nexus·2026
Same journal

Vanin-1 deficiency enhances host tolerance to influenza infection by modulating cellular redox status.

PNAS nexus·2026
查看所有相关文章

相关实验视频

Updated: Jan 17, 2026

A Tactile Automated Passive-Finger Stimulator TAPS
19:44

A Tactile Automated Passive-Finger Stimulator TAPS

Published on: June 3, 2009

14.2K

贝叶斯估计得出了反韦伯变异性的结果.

Arthur Prat-Carrabin1, Samuel J Gershman1

  • 1Department of Psychology and Center for Brain Science, Harvard University, Cambridge, MA 02138, USA.

PNAS nexus
|September 22, 2025
PubMed
概括
此摘要是机器生成的。

人类的感知显示较大数字的变化较小,挑战了传统的心理物理学. 这种"反韦伯行为"在贝叶斯模型和人类受试者中被观察到,这表明自然先验影响知觉.

更多相关视频

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

10.3K
A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
08:12

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

Published on: March 1, 2022

2.9K

相关实验视频

Last Updated: Jan 17, 2026

A Tactile Automated Passive-Finger Stimulator TAPS
19:44

A Tactile Automated Passive-Finger Stimulator TAPS

Published on: June 3, 2009

14.2K
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

10.3K
A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
08:12

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

Published on: March 1, 2022

2.9K

科学领域:

  • 认知心理学 认知心理学
  • 心理物理学的精神物理.
  • 计算神经科学是一种神经科学.

背景情况:

  • 人类的感知通常表现出韦伯行为,其中响应变化随着刺激大小的增加而增加.
  • 著名的贝叶斯观念观念范式并没有广泛关注韦伯行为.
  • 以前的模型通常假定线性编码,未能捕捉某些感知模式.

研究的目的:

  • 与人类实验对象相比,研究贝叶斯观察者的变性.
  • 检查操纵先前分布和奖励函数如何影响感知变化.
  • 调和观察到的感知模式与既定的心理物理原理和贝叶斯框架.

主要方法:

  • 进行了两个预先注册的实验,涉及到数量估计任务.
  • 操纵了数字的先验概率分布.
  • 改变了与准确估计相关的奖励函数.
  • 对比人类对贝叶斯观察者模型预测的反应.

主要成果:

  • 贝叶斯观察者表现出"反韦伯行为" (较大数量的变化较少),当大数量更频繁或更有回报时.
  • 人类对象表现出类似的反韦伯行为,与经典的心理物理发现相矛盾.
  • 受试者的反应最好通过对数的对数编码来解释,与费克纳的建议保持一致.

结论:

  • 人类的感知可以表现出反韦伯的行为,挑战长期的心理物理结果.
  • 贝叶斯模型在特定条件下 (例如,倾斜的先验) 可以复制这种反韦伯行为.
  • 以前与韦伯行为相关的对数编码在这种情况下与反韦伯行为兼容.
  • 自然先验的倾斜性被认为是感知变化增加的主要驱动因素.