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相关概念视频

Social Loafing01:37

Social Loafing

34.8K
Another way in which a group presence can affect performance is social loafing—the exertion of less effort by a person working together with a group. Social loafing occurs when our individual performance cannot be evaluated separately from the group. Thus, group performance declines on easy tasks (Karau & Williams, 1993). Essentially individual group members loaf and let other group members pick up the slack. Because each individual’s efforts cannot be evaluated,...
34.8K
Variation01:19

Variation

6.8K
An important characteristic of any set of data is the variation in the data. In some data sets, the data values are concentrated closely near the mean; in other data sets, the data values are more widely spread out from the mean. The most common measure of variation, or spread, is the standard deviation, which is the square root of variance.
When independent and dependent variables are plotted on a scatter plot, the slope of a line is a value that describes the rate of change between the two...
6.8K
Regression Toward the Mean01:52

Regression Toward the Mean

6.3K
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
Testing a Claim about Standard Deviation01:19

Testing a Claim about Standard Deviation

2.5K
A complete procedure to test a claim about population standard deviation or population variance is explained here.
The hypothesis testing for the claim of population standard deviation (or variance) requires the data and samples to be random and unbiased. The population distribution also must be normal. There is no specific requirement on the sample size as the estimation is based on the chi-square distribution.
As a first step, the hypothesis (null and alternative) concerning the claim about...
2.5K
Saint-Venant's Principle01:18

Saint-Venant's Principle

702
The principle of Saint-Venant postulates that the stress distribution within a structural member does not rely on the precise method of load application except in the vicinity of the load application points. Consider a scenario where loads are centrally applied on two plates. In this case, the plates move toward each other without any rotation. This movement causes the member to contract in length and expand in width and thickness. Uniform deformation across all elements and maintaining...
702
Noncompartmental Analysis: Statistical Moment Theory00:56

Noncompartmental Analysis: Statistical Moment Theory

138
Noncompartmental analyses leverage statistical moment theory to examine time-related changes in macroscopic events, encapsulating the collective outcomes stemming from the constituent elements in play. Statistical moment theory is a mathematical approach used to describe the time course of drug concentration in the body without assuming a specific compartmental model. SMT provides insights into drug absorption, distribution, metabolism, and elimination by treating drug concentration versus time...
138

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相关实验视频

Updated: Jul 23, 2025

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

Published on: July 3, 2020

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增加回报的大偏差理论

Simone Franchini1, Riccardo Balzan1

  • 1Sapienza Universitá di Roma, Piazza A. Moro 1, 00185 Roma, Italy.

Physical review. E
|July 19, 2023
PubMed
概括

本研究分析了带有增长回报的通用化市场模型,揭示了预期锁定阶段的亚线性成本. 我们确定了最可能的市场份额轨迹和市场动态的非线性微分方程.

科学领域:

  • 经济学 经济学 经济学
  • 数学经济学数学经济学
  • 统计物理 统计物理

背景情况:

  • 增加回报理论解释了市场与竞争产品的锁定.
  • 亚瑟的模型表明,一个产品通过多数机制成为断.
  • 现有的模型缺乏对概率客户选择的分析.

研究的目的:

  • 用概率客户选择分析市场竞争的概括模型.
  • 调查市场份额动态,并确定可能的发展轨迹.
  • 探索系统在预期锁定区域的行为.

主要方法:

  • 在样本路径层面进行大偏差分析.
  • 为最可能的市场份额轨迹推导公式.
  • 对积累生成函数的非线性微分方程的分析.

主要成果:

  • 确定了一个亚线性成本区域,预计将锁定.
  • 推导出一个公式来确定最可能的市场份额演变.
  • 建立了一个非线性微分方程来规范市场份额动态.

结论:

  • 一般化的模型表现出复杂的动态,超出了简单的锁定.

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  • 概率主义的客户行为可能会导致意想不到的融合模式.
  • 该研究提供了分析市场份额波动和稳定性的工具.